Population Changes and Healthcare Delivery in Ebonyi State, Nigeria

Population Changes and Healthcare Delivery in Ebonyi State, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Population Changes and Healthcare Delivery in Ebonyi State, Nigeria Agatha Arochukwu, Felix Ike, Adelowo Adefisayo Adewoyin, Adebayo Eludoyin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5758809/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 16 You are reading this latest preprint version Abstract This study investigates the population dynamics of healthcare delivery in Ebonyi State, Nigeria, emphasising gender disparities, spatial distribution, and the accessibility of basic health facilities, employing Geographic Information Systems (GIS) for analysis. The research reveals that Izzi, Onicha, Ikwo, and Ohaukwu Local Government Areas (LGAs) collectively account for over 40% of the state's population. Demographic data indicates a 2.8% annual population growth across the 13 LGAs from 2006 to 2022, with Ivo LGA, the least populated, representing approximately 4.6% of the state's population. The GIS analysis indicates that 81.1% of the population resides within 60 minutes of a primary healthcare centre (PHC), though accessibility varies significantly, especially in rural areas. The gender distribution shows an overall balance with 49% males and 51% females; however, LGAs such as Izzi and Ikwo exhibit a higher proportion of females than males. These findings underscore the necessity for targeted healthcare interventions, including equitable resource allocation, enhancement of PHC facilities, and the provision of gender-sensitive services such as maternity and pediatric care. The GIS-based accessibility mapping highlights the importance of incorporating spatial analysis into healthcare planning to identify underserved areas and optimise resource allocation. This study provides essential data for developing population-centered, spatially aware, and sustainable healthcare policies in Ebonyi State, thus serving as a valuable resource for international health researchers and policymakers. Population dynamics GIS analysis healthcare accessibility Ebonyi State spatial distribution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Understanding population growth, health, and resource demands necessitates a comprehensive analysis of demographic dynamics, encompassing the size and composition of the human population over time. Key drivers of population growth include birth rates, death rates, age distribution, fertility, and gender balance (Rotella et al., 2021 ). Among these, birth and death rates are particularly critical. Birth rates, measured as births per thousand individuals or females over a specific period, are used to calculate fertility rates the average number of children born over a given time (Nash, 2019 ). Conversely, death rates provide insights into the impact of human survival on population growth by indicating the rate of deaths within a community over a certain period. Significant global demographic shifts are reshaping the demographic environment, particularly in age distribution, growth patterns, and population composition (Gu et al., 2021 ; Snyder et al., 2023 ). Gao & O'Neill (2020) highlight unprecedented variations within and among countries due to global population changes, leading to severe geographical and age-related differences. In more developed countries, fertility and ageing patterns have resulted in older population structures, whereas population growth remains a major concern in developing countries (Atoyebi &Anuodo, 2018). According to Gu et al. ( 2021 ), the global population is projected to increase from over 7 billion in 2011 to over 9 billion by 2050, significantly impacting healthcare delivery systems worldwide. In Nigeria, rapid population growth has intensified pressure on healthcare services, particularly at the primary healthcare level (Ebingha et al., 2019 ). The Nigeria Population Council (NPC, 2020) projected that the population would increase from 188 million in 2016 to over 218 million by 2022 and beyond. Like many regions in sub-Saharan Africa, Ebonyi State faces challenges related to the unpredictable increase in population and healthcare service quality. Temporal and spatial fluctuations in population size, variation, and socioeconomic characteristics exacerbate these challenges. Urbanization, population growth, and rural-urban migration are significant factors influencing the distribution of healthcare facilities, the need for healthcare services, and resource allocation. The NPC (2020) recorded that Ebonyi State's population is expected to grow at an annual rate of 2.8%, from 2.1 million in 2006 to over 3 million by 2022. Although total fertility rates (TFRs) in Nigeria have declined gradually from 6.7 in 2008 to 5.3 in 2018, the reduction rate remains high compared to advanced countries (Obiyan et al., 2019 ). Population growth in Ebonyi State has significantly impacted healthcare accessibility, marked by high fertility levels and a slight reduction in TFRs. This is particularly prevalent in rural areas where primary health care (PHC) remains the primary point of contact with the health system (Nwakamma et al., 2024 ). Gizaw et al. ( 2022 ) explain that the objective of PHC is to provide community-based, essential, and readily accessible healthcare. The World Health Organization (WHO) Alma-Ata Declaration of 1978 emphasized the importance of PHC in ensuring inclusive healthcare access, especially for marginalized populations (WHO, 2019). Studies support the effectiveness and efficiency of comprehensive PHC systems, which are associated with better healthcare outcomes, lower costs, and fewer hospitalizations for preventable diseases (Haque et al., 2020 ; Mrejen et al., 2021). Affordable healthcare services and improved quality are consistently linked to robust PHC systems. Despite significant urban development in Ebonyi State, rural regions still struggle to access adequate healthcare services due to staff shortages, poor transportation networks, and inadequate infrastructure (Onwujekwe& Nwali, 2022 ). The disparity between rural and urban healthcare facilities is exacerbated by easier access to healthcare services in urban areas. The state has seen a shift towards a younger population structure, with a significant percentage of individuals under 15. This demographic shift has heightened the demand for specialized services such as immunization, reproductive health care, and mental health support (Onwujekwe& Nwali, 2022 ). The nexus between population dynamics and healthcare delivery is a vital component of public health planning and management. Understanding temporal and spatial population distribution is crucial to ensuring equitable access to healthcare systems. This research aims to determine the dynamics impacting accessible healthcare provision in Ebonyi State, Southeastern Nigeria, and examine the relationship between PHC facility availability, accessibility, and service provision concerning population dynamics. Study Area Ebonyi State, created in 1996 from parts of Enugu and Abia States, is located in southeastern Nigeria. It shares borders with Cross River State to the east, Benue State to the north, Enugu State to the west, and Abia State to the south (Fig. 1 ). According to the National Population Council (NPC) census of 2006, the population of Ebonyi State was recorded at 2,176,947 (NPC, 2020). Geographically, Ebonyi State lies between latitudes 5° 40' 0" N and 6° 15' 18" N and longitudes 7° 40' 55" E and 8° 05' 55" E. The state covers a land area of approximately 5,533 km² within Nigeria's Southeast geopolitical zone (Anikwe et al., 2020 ). The state is predominantly inhabited by the Igbo tribe and comprises 13 Local Government Areas (LGAs). Annual rainfall in Ebonyi ranges between 1300 mm and 2000 mm, with peak precipitation occurring from July to October. The average daily maximum temperature from January to May fluctuates between 27°C and 35°C (Amadi et al., 2019 ). The vegetation in Ebonyi State is primarily categorized into three major types: rainforest, tall grass savannah, and woodland. Additionally, the state features freshwater swamps and mangroves in certain areas. Agriculture is the mainstay of Ebonyi State's economy, with over 85% of the population engaged in agricultural activities. The state produces various cash crops such as oil palm, cashew, cocoa, and rubber. Staple crops include rice (locally branded as Abakaliki rice), yam, cassava, maize, cocoyam, cowpea, and groundnut. The state also engages in fishing and livestock rearing as primary means of livelihood. The state is rich in natural resources, including salt, zinc, lead, kaolin, limestone, and other minerals, which support small-scale industries and crafts such as blacksmithing and pottery (Ezeh et al., 2022 ). Materials and Methods Data collection A mixed-method approach was employed, incorporating both qualitative and quantitative data collection methods. Data were sourced from both primary and secondary sources. The primary data were collected from PHCs, human resources, medical equipment, and infrastructure through field surveys and GIS methods. The data were obtained using the National Primary Health Care Development Agency's checklist for minimum criteria in PHC delivery in Nigeria (NPHCDA, 1995, 2012). In addition, secondary data were obtained from OpenStreetMap, the Ebonyi State Primary Health Care Development Agency, and the National Population Commission. Additional data, such as road networks, administrative maps, asset lists, and demographic information, were retrieved from the Nigerian Geospatial Data Infrastructure (NGSDI) and fieldwork. Data on facility availability were gathered through physical assessments of infrastructure, staffing, and service delivery compliance with the Minimum Standards Checklist of Primary Health Centers in each of the 171 PHCs in Ebonyi State. Analysis The study explored access to healthcare services and the preparedness of PHC facilities in the study area. Data were analyzed using Euclidean distance, Network Analysis, Cost Distance Analysis, and Provider-to-Population Ratio (PPR). Euclidean Distance and Network Analysis were used to analyze distances. Euclidean distance \(\:\left(\text{e}\text{q}.\:1\right)\) Calculates the straight-line distance between relevant points, such as a residence and the nearest health service site (Guagliardo, 2004 ). $$\:d=\sqrt{{\left({x}_{2}-{x}_{1}\right)}^{2}+{\left({y}_{2}-{y}_{1}\right)}^{2}}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(1\right)$$ Where d is the Euclidean distance \(\:\left({x}_{1},\:{y}_{1}\right)\) Are the coordinates of the first point, and \(\:({x}_{2},\:{y}_{2})\) Are the coordinates of the second point? Euclidean distance was specifically used to calculate spatial accessibility in rural areas of Ebonyi State, where access to motorized transportation routes is limited (Masoodi & Rahimzadeh, 2015 ; Noor et al., 2006 ; Snyman & Coetzee, 2024 ). Network analysis \(\:\left(\text{e}\text{q}.\:2\right)\) Was used to calculate trip times or distances using real transport routes. $$\:{T}_{mn}=\frac{{L}_{m}\times\:60}{{S}_{km/h}\times\:1000}\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\left(2\right)$$ Where \(\:{T}_{mn}\) Is the cost in minutes of travelling over the road or road section, \(\:{L}_{m}\) Is the length of the section in meters, and \(\:{S}_{km/h}\) Is the speed limit in km/h (Ouma et al., 2021 )? In addition, cost distance analysis calculates journey time, considering variables such as road types, land covers, and elevation. This method provides a means of determining access by developing a cost surface that estimates travel speed on various land cover types (Zhang et al., 2021 ). It is sensitive to spatial resolution and generally works well in Sub-Saharan Africa, where most accessibility decisions are determined by distance (Pu et al., 2020 ). This study generated a cost surface, defining travel speeds within various land covers, roads, and elevations in the study area. This surface was then combined with the spatial distribution of health facilities in a cost-distance analysis to create a surface showing the shortest time needed to get to each health facility for each populated location. The PPR, also referred to as supply ratios, was computed within bordered areas (Guagliardo, 2004 ). This ratio calculates the accessibility of healthcare by dividing the number of medical facilities, physicians, or beds in an administrative region by the population of that area (Ouma et al., 2021 ). While simple and helpful for identifying service shortages, PPR ignores factors that affect travel, such as elevation, distance, and the availability of transportation (WHO, 2019; Ouma et al., 2021 ). In this study, PPR was used to highlight differences between administrative boundaries of health facilities and identify gaps in service delivery. GIS Analysis ArcGIS by ESRI was utilized as a powerful geographical information system (GIS) tool for advanced mapping and spatial analysis (Fleming et al., 2022 ). Geographical accessibility was processed and mapped using the Network Analyst extension add-in, specifically the Service Area (SA) component. Shapefiles and PHC locations projected to the proper coordinate systems ensured accurate spatial distance analysis. This integration allowed for an in-depth evaluation of healthcare accessibility and resource distribution. The Digital Elevation Model (DEM) for Ebonyi State, derived from the Aster GDEM 2011 with a spatial resolution of 30 meters, was used to calculate walking times. The analysis assumed uniform road types across the study area and employed QGIS open-source software (Geospatial Foundation Project, 2015). An administrative map from the National Population Commission defined the study area, representing the division of Ebonyi State into 13 LGAs. Mapping and modelling of the road network dataset, also obtained from the National Population Commission, identified restricted vehicle movement areas. Additional road segments were digitized using Google Earth to address topological problems in the dataset. The improved road network and PHC facility locations were then assessed using ArcGIS software to enhance the precision of spatial modelling. This methodology enabled an accurate assessment of PHC facility accessibility, considering topography and infrastructure limitations. Results Population changes Table 1 presents the population distribution across the 13 Local Government Areas (LGAs) of Ebonyi State as of 2022, detailing the trends in gender distribution and the percentage contribution of each LGA to the state's total population. The most populous LGAs are Izzi, Onicha, Ikwo, and Ohaukwu, each with an approximate population of 300,000. Specifically, Izzi LGA has the largest proportion, accounting for approximately 13.8% of the state's population, followed by Ikwo and Onicha with 11.5% and 9.2%, respectively. In contrast, Ivo LGA has a population of 188,789, contributing 4.6% to the state's total population. These population discrepancies highlight the need for targeted healthcare interventions, particularly due to the demographic differences between densely and sparsely populated areas. Table 1 Estimated population distribution by gender within the local government areas in Ebonyi State as of2022 LGA Total Male Female Ratio of total male (%) Ratio of total female (%) % distribution across LGA Abakaliki 232843 112807 120036 48 52 18.4 Afikpo North 243679 125429 118250 54 51 6.9 Afikpo South 245068 123035 122033 53 52 5.5 Ebonyi 197909 93938 103971 40 45 9.1 Ezza North 227345 109420 117925 47 51 8.3 Ezza South 207863 103248 104615 44 45 7.8 Ebonyi 197909 93938 103971 40 45 9.1 Ikwo 334400 155332 179068 67 77 11.5 Ishielu 237351 113045 124306 49 53 6.4 Ivo 188789 96522 92267 41 40 4.6 Izzi 368171 175518 192653 75 83 13.8 Ohaozara 230718 116812 113905 50 49 7.4 Ohaukwu 304200 146969 157231 63 68 5.5 Onicha 368062 183296 184766 79 79 9.2 The population of Ebonyi State is fairly balanced, with 51% females and 49% males. However, within each Local Government Area (LGA), this varies significantly. For instance, Izzi and Ikwo LGAs have a much higher proportion of females, while Afikpo South has a more balanced gender distribution. The demographic diversity across the state is also reflected in the proportion of each LGA's contribution to the state's total population. As the most populous LGA, Izzi contributes 13.8% to the total population, whereas Ivo, the least populous, accounts for only 4.6%. Ebonyi LGA lies in the middle of the state's population distribution, accounting for 9.1% of the total population. These variations indicate different health requirements across LGAs. Densely populated areas necessitate more medical equipment, personnel, and healthcare facilities to meet the growing demand for services. In Ivo LGA, the gender ratio is relatively balanced, with 41% men and 40% women. However, the significant disparity in the number of females to males in LGAs such as Izzi and Ikwo could be attributed to regional variations in fertility rates, migration, or other socioeconomic factors. These population trends have significant healthcare implications. LGAs like Izzi and Ikwo, with increasing populations, require more healthcare services, including larger facilities, more staff, and additional medical supplies. The higher proportion of females in these areas necessitates an increased focus on maternity, reproductive, and family planning services. Additionally, pediatric care, vaccination campaigns, and other preventive healthcare measures must be prioritized, given the young population in many LGAs. Although the elderly make up only about 5% of the population, they cannot be overlooked, especially as the population ages and grows. The uneven population distribution in Ebonyi State leads to higher healthcare costs in densely populated areas such as Izzi and Ikwo. Changes in gender distribution highlight the need for tailored health services for men and women based on their specific needs. Effective health planning and resource allocation are crucial to ensure that, as the population of Ebonyi State increases, all residents, particularly those in high-density areas, receive appropriate healthcare services. Distribution by gender Table 2 presents the percentage distribution of the population by sex ratio across the 13 Local Government Areas (LGAs) in the study area. Notably, 71% of the LGAs have an even distribution of males and females. Izzi and Onicha LGAs stand out with the highest percentages of male and female residents, each accounting for 11% of their respective totals, indicating high population densities. Ohaukwu and Ikwo LGAs also show significant population concentrations, with Ohaukwu accounting for 9% of the male population and Ikwo contributing between 8–10% of the total population. In contrast, Ivo LGA is the least densely populated area, comprising only 6% males and 5% females. The overall gender mix in Ebonyi State is predominantly female, with a male-to-female ratio of 49–51%. This balanced gender distribution underscores the state's stable population dynamics and has important implications for planning and implementing equitable policies and resource allocations. For example, densely populated LGAs like Izzi and Onicha may need to prioritize healthcare and social services to cater to their larger populations. Additionally, the higher proportion of females in these areas suggests a greater need for maternity, reproductive, and family planning services. Ensuring the appropriate allocation of medical equipment, personnel, and facilities in these LGAs is crucial to meeting the healthcare demands of their residents. In summary, understanding the demographic characteristics of Ebonyi State, particularly the population distribution and gender ratios, is essential for effective healthcare planning and resource allocation. This approach will help address the varying health needs across different LGAs, ensuring equitable access to healthcare services for all residents. Table 2 Percentage distribution of the population by gender across the State LGA TOTAL Male Female Ratio of total male (%) Ratio of total female (%) Abakaliki 232843 1128067 120036 7 7 Afikpo North 243679 125429 118250 8 7 Afikpo South 245068 123035 122033 7 7 Ebonyi 197909 93938 103971 6 6 Ezza North 227345 109420 117925 7 7 Ezza South 207863 103248 104615 6 6 Ebonyi 368171 175519 192653 11 11 Ikwo 368062 183296 184766 11 11 Ishielu 232843 1128067 120036 7 7 Ivo 243679 125429 118250 8 7 Izzi 245068 123035 122033 7 7 Ohaozara 197909 93938 103971 6 6 Ohaukwu 227345 109420 117925 7 7 Onicha 207863 103248 104615 6 6 Distribution by age group Table 3 presents the percentage distribution of the Ebonyi State population by age group, revealing significant demographic trends. The population is predominantly young, with over 51% under 20 years old. There is substantial workforce potential, as 44% of the population is within the prime working age of 20 to 59 years. The elderly population, those over 60 years old, constitutes only 5%, indicating a relatively small proportion. The data illustrate that the population gradually decreases with increasing age, with younger age groups significantly larger compared to older ones. Interestingly, there are more women than men in the older age groups, while men dominate the population under 20 years old. This has important implications for education, employment, and health planning, particularly in areas such as maternity and child health and support for the ageing population. The demographic composition is consistent with trends in sub-Saharan Africa, where populations tend to be younger. Approximately 5% of the population is 60 or older, highlighting the growing need for healthcare services for an ageing population in the coming decades. Additionally, the significant proportion of younger individuals suggests a greater demand for maternal and paediatric care services. Understanding these demographic characteristics is crucial for effective healthcare planning. The young demographic composition of Ebonyi State underscores the necessity for targeted health interventions and resource allocations to meet the diverse needs of its population. This approach will ensure that, as the population grows, particularly in younger and ageing segments, all residents receive the appropriate healthcare services. Table 3 Percentage Distribution by Age Group Age Male Female Total %Male %Female %Total 0–4 225975 219695 445670 15 13.64 14.14 5–9 215324 211050 426374 13.96 13.11 13.52 10–14 208222 205602 413824 13.50 12.77 13.13 15–19 186703 189164 375867 12.11 11.75 11.92 20–24 139583 132647 272230 9.05 8.24 8.64 25–29 100907 110873 211780 6.54 6.88 6.72 30–34 84103 99375 183478 5.45 6.17 5.82 35–39 76446 95307 171753 4.96 5.92 5.45 40–44 71003 80476 151479 4.60 5.00 4.81 45–49 61766 71519 133285 4.01 4.44 4.23 50–54 48727 50897 99624 3.16 3.16 3.16 55–59 38293 44901 83193 2.48 2.79 2.64 60–64 30162 35882 66044 1.96 2.23 2.09 65–69 23752 29152 52905 1.54 1.81 1.68 70–74 14642 16857 31499 0.95 1.05 1.00 75–79 10819 10542 21362 0.70 0.65 0.68 80+ 5668 6494 12161 0.37 0.40 0.39 Accessibility to Primary Health Care Facilities The study on accessibility to primary health care (PHC) facilities revealed that 81.1% of villages in Ebonyi State could reach a PHC within 60 minutes, and 63.1% of villages are within a 10-minute driving distance, as depicted in Fig. 2 . Conversely, 18.9% of communities are considered underserved, lying outside the 60-minute travel criterion, as shown in Fig. 3 . Accessibility varies significantly across different Local Government Areas (LGAs). LGAs such as Ishielu, Izzi, Afikpo North, and Afikpo South face challenges in accessibility due to inadequate road infrastructure and longer travel distances. In contrast, LGAs such as Abakaliki, Ebonyi, Ezza North, and Ohaukwu have the majority of locations fully accessible to PHCs by car. This disparity underscores the need for targeted interventions to improve road infrastructure and reduce travel time to healthcare facilities in underserved areas. Enhancing accessibility to PHCs is crucial for ensuring equitable healthcare delivery and meeting the health needs of all residents in Ebonyi State. Addressing these accessibility issues will involve strategic planning and investment in infrastructure development, particularly in LGAs with poor access to healthcare services. This approach will contribute to the overall improvement of healthcare outcomes and the well-being of the population in Ebonyi State. Walking and Driving Scenarios for Underserved and Served Areas Figures 3 and 4 compare walking and driving scenarios for underserved and served areas. While driving offers quicker access, a significant portion of the rural population still relies on walking as their primary mode of transportation due to the scarcity of motorized vehicles. The maps illustrate that underserved areas are more readily identifiable on foot, although, in some regions, it can take over an hour to walk to a primary healthcare centre (PHC). Notably, this includes villages in Izzi, Ishielu, and parts of Ohaukwu. These findings highlight the need for strategic interventions to improve accessibility, such as enhancing transportation infrastructure and increasing the availability of motorized transport in rural areas. Ensuring that all residents can access healthcare services within a reasonable timeframe is crucial for the overall health and well-being of the population in Ebonyi State. For the walking scenario (Fig. 4 ), using the same time intervals as in the driving scenario, it was found that approximately 42.1% of the villages are located within a 10-minute walk from PHCs. This percentage decreases significantly to 21.0% for villages within a 50-minute walking distance. Overall, 63.1% of the population can reach a PHC within a 60-minute walk. However, 37.9% of the villages typically require more than 60 minutes to walk to a PHC, indicating that these villages are underserved. Figure 5 illustrates the service area for walking time to PHCs in Ebonyi State.These findings emphasize the need for targeted interventions to improve accessibility, such as developing transportation infrastructure and increasing the availability of motorized transport in rural areas. Ensuring that all residents can access healthcare services within a reasonable timeframe is crucial for the overall health and well-being of the population in Ebonyi State. Comparison with the Minimum Standard Checklist for PHCs The assessment of the spatial distribution and adequacy of public health facilities across Ebonyi State reveals significant disparities in the delivery of primary health care (PHC) services. Health planners aim to ensure that administrative units are equipped with the necessary number of public health facilities and adequate resources, including physical infrastructure, human resources, and medical care for the community served. In the study area, Ikwo LGA has a total of 20 PHC facilities, making it the largest in Ebonyi State, followed by Ishielu with 16 facilities. Izzi has thirteen, while Abakaliki and Ohaukwu each have fifteen facilities. Other LGAs, including Afikpo North, Ebonyi, and Onicha, also have PHC facilities. However, LGAs such as Ohaozara, Ivo, Ezza South, Ezza North, and Afikpo South each have 11 facilities. This distribution indicates that many regions are inadequately equipped with primary health facilities and health-related human resources, resulting in uneven coverage and accessibility issues. The number of PHC facilities and Human Resources for Health (HRH) per 10,000 population is a standardized metric for measuring the accessibility of healthcare services. As shown in Table 4 , several LGAs have less than one PHC facility per 10,000 population, indicating poor service coverage. For example, Ebonyi and Abakaliki LGAs have 0.8 PHC facilities per 10,000 population, compared to 0.7 in Ishielu and Ezza North. HRH is remarkably scarce throughout the state; only a few LGAs have one health worker per 10,000 residents. Ebonyi, Afikpo South, and Ikwo are among the LGAs with the lowest ratios of 0.1, while Ezza North has the highest ratio at 0.2 per 10,000. This deficiency highlights the urgent need to increase the number of PHCs and HRHs to meet the population's health demands. Table 4 PHC facilities and HRH per 10,000 population Lga Total Sampled PHC PHC Pop Average PHC/ 10,000 Population Average HRH/ 10,000 Population Abakaliki 15 185679 0.8 0.1 Afikpo North 12 80391 1.4 0.1 Afikpo South 11 96614 1.1 0.1 Ebonyi 12 142055 0.8 0.1 Ezza North 11 143588 0.7 0.2 Ezza South 11 70772 0.1 0.2 Ikwo 20 114641 1.7 0.1 Ishielu 16 207077 0.7 0.2 Ivo 11 102163 0.4 0.1 Izzi 13 116754 1.1 0.1 Ohaozara 11 127214 0.8 0.1 Ohaukwu 15 125382 1.9 0.1 Onicha 12 86876 1.3 0.1 Availability of Medical Equipment and Physical Infrastructure in PHCs The availability of medical equipment and physical infrastructure in primary healthcare centers (PHCs) is crucial for effective service delivery. Table 5 indicates that the availability of medical equipment across all Local Government Areas (LGAs) is less than 50%. Afikpo North has the highest proportion of available medical equipment at 37.6%, while Onicha has the lowest at 30.7%. The availability of physical infrastructure also varies significantly, with Izzi at 51.7% and Ebonyi at 41.3%. These deficiencies highlight a general lack of resources needed to provide quality primary health services.When comparing the availability of medical equipment, Ebonyi South is relatively higher compared to Ebonyi North and Ebonyi Central, with proportions of 34.0%, 30.0%, and 33.6%, respectively. For physical infrastructure, Ebonyi Central accounts for 43.8%, Ebonyi North 44.0%, and Ebonyi South 40.8%. Despite these regional differences, the overall availability of resources remains below the minimum standards required for effective healthcare delivery. PHC Service Readiness The provision of quality healthcare depends on the readiness of services, which includes facilities, tools, and personnel. Table 6 demonstrates that PHC facilities across LGAs vary in their capacity to serve their estimated populations. For instance, Ezza North serves 131% of its predicted population, indicating an overstretched facility, whereas Ikwo serves only 57% of its population, signifying underutilization.Human resources for health (HRH) are remarkably scarce throughout the state, with availability ranging from 15% in Ezza North to as low as 6% in Ikwo. The availability of medical equipment also varies, from 30.7% in Onicha to 37.6% in Afikpo North, which is inadequate. The inadequacy of resources is further demonstrated by the availability of physical infrastructure, with Izzi having the highest at 50.1%, while Afikpo South has the lowest at 41%.These disparities in healthcare access and resource availability highlight the urgent need to increase the number of PHCs and HRHs to meet the health demands of the population. Addressing these gaps will ensure more equitable healthcare access and improve the overall efficiency of healthcare delivery in Ebonyi State. Table 5 Availability of Medical Equipment and Physical Infrastructure in PHCs LGA Medical Equipment Physical Infrastructure Required Available % Available Required Available % Available Abakaliki 5655 1793 31.7 390 163 41.8 Afikpo North 4524 1699 37.6 312 136 43.6 Afikpo South 4147 1479 35.7 286 126 44.1 Ebonyi 4524 1487 32.9 312 129 41.3 Ezza North 4147 1431 34.5 286 134 46.9 Ezza South 4147 1445 34.8 286 122 42.7 Ikwo 7540 2582 34.2 520 225 43.3 Ishielu 6032 1884 31.2 416 179 43.0 Ivo 4147 1344 32.4 286 133 46.5 Izzi 4901 1685 34.4 338 170 50.3 Ohaozara 4147 1389 33.5 286 148 51.7 Ohaukwu 5655 1875 33.2 390 167 42.8 Onicha 4524 1388 30.7 312 150 48.1 Table 6 PHC Service Readiness in Ebonyi State by LGA LGA PHC Population Human Resources Medical Equipment Physical Infrastructure Sampled PHC Required Population (‘000) Available % of Population Required Available % Available Required Available % Available Required Available % Available AfikpoNorth 12 120 80391 67 288 40 14 4524 1699 37.6 312 136 43.6 Afikpo South 11 110 96614 88 264 36 14 4147 1479 35.7 286 126 44.1 Ivo 11 110 102163 93 264 26 10 4147 1344 32.4 286 133 46.5 Ohaozara 11 110 127214 116 264 23 9 4147 1389 33.5 286 148 51.7 Onicha 12 120 86876 72 288 30 10 4524 1388 30.7 312 150 48.1 Abakaliki 15 150 185679 124 360 38 11 5655 1793 31.7 390 163 41.8 Ebonyi 12 120 142055 118 288 26 9 4524 1487 32.9 312 129 41.3 Izzi 13 130 116754 90 312 23 7 4901 1685 34.4 338 170 50.3 Ohaukwu 15 150 125382 84 360 36 10 5655 1875 33.2 390 167 42.8 Ezza North 11 110 143588 131 264 40 15 4147 1431 34.5 286 134 46.9 Ezza South 11 110 70772 64 264 63 24 4147 1445 34.8 286 122 42.7 Ikwo 20 200 114641 57 480 29 6 7540 2582 34.2 520 225 43.3 Ishielu 16 160 207077 129 384 60 16 6032 1884 31.2 416 179 43.0 Discussion This study comprehensively examines the spatial accessibility, resource availability, and service preparedness of primary healthcare (PHC) institutions in Ebonyi State, Nigeria, highlighting significant gaps in the pursuit of equitable healthcare. It reveals marked disparities in the distribution of PHC facilities, staff, medical supplies, and physical infrastructure, reflecting broader systemic obstacles to achieving Universal Health Coverage (UHC).The spatial accessibility analysis demonstrated that most Local Government Areas (LGAs) fell below the threshold of having one PHC facility per 10,000 people, although certain LGAs, such as Ikwo and Ohaukwu, have higher ratios. These disparities, particularly pronounced between the northern and central zones, underscore the unequal distribution of healthcare resources in underprivileged areas. This finding is consistent with international research indicating that geographic proximity to health facilities can improve health outcomes and utilization rates (WHO, 2019). The study highlights a severe shortage of human resources for health, with most LGAs reporting less than one health worker per 10,000 inhabitants. Additionally, the average availability of medical equipment across the state is less than 50%, compounded by inadequate physical infrastructure. These deficiencies are particularly acute in Ebonyi North and Central Senatorial Districts, which have dense populations further straining the limited available resources. This pattern aligns with national trends in Nigeria, where chronic underinvestment in health staffing and facilities disproportionately affects rural areas, exacerbating health disparities. Disparities in service readiness and resource distribution also reflect systemic inefficiencies in health planning and governance. For example, the very low utilization rates of PHC facilities in LGAs such as Ikwo contrast sharply with overcrowding in LGAs such as Ezza North and Abakaliki, where population coverage exceeds 120%. This underscores the need for a more strategic, data-driven approach to resource distribution, considering geography and population dynamics in health policy decisions. Strengthening PHC systems to enhance service readiness is crucial, as shortages in amenities, diagnostic equipment, and human resources hinder the ability of PHC facilities to offer comprehensive services. These deficits also undermine the state's capacity to respond effectively to emergencies, posing challenges to achieving UHC by 2030 (Arthur, 2023 ). The study further establishes that health service delivery interacts with population dynamics. The high population growth rates and preponderance of young people in Ebonyi State drive increasing demand for maternity and child health services, as well as interventions for both communicable and non-communicable diseases. Addressing these challenges requires increased hiring and training of healthcare professionals, adequate medical equipment, and sustained investments in PHC infrastructure. Comparing these findings with those from other African countries and the Western world reveals both convergences and divergences. The 2.8% annual population growth rate in Ebonyi aligns with the general trend in Sub-Saharan Africa, characterized by rapidly growing populations that strain health systems (Gu et al., 2021 ; Adeleye et al., 2023 ). In contrast, Western countries face slower population growth and aging populations. Urbanization and high fertility rates in Ebonyi outpace infrastructure development, creating additional challenges. Gender dynamics in Ebonyi, similar to other African countries like South Africa and Ethiopia, show higher healthcare needs for women due to reproductive health issues (Ninsiima et al., 2021 ; Admassu et al., 2022 ; Mbachu et al., 2022). In the West, research focuses more on mental health disparities, such as the higher prevalence of depression among females, which can be more effectively treated due to better access to healthcare services. Regarding healthcare accessibility, 81.1% of the population in Ebonyi State can access PHCs within a 60-minute travel time, similar to Kenya (Oliphant et al., 2021 ). However, disadvantaged districts remain, highlighting the need for targeted interventions. While access to healthcare is also a challenge in some Western areas, such as Appalachia, these regions often have better infrastructure compared to rural areas in Ebonyi (Eberth et al., 2022 ). In all, the study underscores critical gaps in healthcare resource provision, including poor provider-to-population ratios and insufficient medical equipment. Western countries like Canada and Germany benefit from better resource distribution and robust healthcare infrastructure, as noted by Marchildon et al. (2022). These comparisons illustrate the urgent need for Ebonyi State to address its rapidly expanding population and resource shortages through improved healthcare policies and facilities. Conclusion and Recommendations This study establishes that PHC facilities across Ebonyi State, Nigeria, are grossly unequal in their spatial accessibility, resource availability, and service readiness. The inequitable distribution of PHC buildings, personnel, medical supplies, and physical infrastructure indicates structural inefficiencies that hinder equitable healthcare provision. While some LGAs, such as Ikwo and Ohaukwu, have relatively good facility-to-population ratios, many LGAs fall below the minimum threshold. Additionally, gaps in facility distribution are particularly evident in the northern and central senatorial zones, exacerbated by high population density and inadequate healthcare infrastructure. The study also reveals significant deficiencies in basic amenities and diagnostic equipment, compounded by low human resources-population ratios, which impair the capacity of PHCs to provide comprehensive care. While some PHC facilities are underutilized, others exceed their prescribed capacity, indicating the need for a more systematic and information-driven approach to health planning and budgeting. Addressing these gaps requires specific funding for PHC infrastructure, equitable resource distribution, and the recruitment and training of medical personnel. Incorporating population dynamics into health policy formulation will ensure that service delivery meets the needs of all areas, particularly disadvantaged ones. Strengthening the PHC system in Ebonyi State is essential to achieving health equity and universal health coverage. Prioritizing poor areas and adhering to equity principles in health planning will ensure access to essential health services for all citizens, promote sustainable development, and assure health equality. Declarations Acknowledgements We would like to thank all the participants in this study. Ethical Consideration Ethical approval for the study was obtained from the Ebonyi State Health Research Ethics Committee. All respondents granted their verbal informed consent, and where required interpretations have been provided to ensure understanding. Funding This project is a self-funding project Author information Author notes Agatha Arochukwu, is the first author, with Felix Ike, Adelowo Adefisayo Adewoyin, & Adebayo Eludoyin as corresponding authors and contributed equally to this work. Authors and Affiliations Contributions Felix Ike and Agatha Arochukwu conceptualized the research. Agatha Arochukwu collects the primary data for this research. Adelowo Adefisayo Adewoyin drafted the manuscript. Felix Ike and Adebayo Eludoyin performed software and method validation. All authors re-reviewed and co-revised the manuscript from the English language perspective. All authors made significant intellectual contributions to multiple revisions of the draft. All authors have read and agreed to the published version of the manuscript. Corresponding authors Agatha Arochukwu, [email protected] Ike Felix, [email protected] Adewoyin A.A, [email protected] O. A. Eludoyin , [email protected] Ethics declarations Ethics approval and consent to participate Ethical approval for the study was obtained from the Ebonyi State Health Research Ethics Committee. All respondents granted their verbal informed consent, and where required interpretations have been provided to ensure understanding. Competing interests The authors declare no competing interests. References Adeleye, O., Adebowale, A., Adeyemo, O., Adeoye, I., Afolabi, R., Fagbamigbe, A., &Palamuleni, M. (2023). Decomposition and spatiotemporal analysis of barriers to healthcare access among women of childbearing age in Nigeria, using Nigeria Demographic and Health Survey from 2003 to 2018. Journal of African Population Studies . Admassu, T. W., Wolde, Y. T., & Kaba, M. (2022). Ethiopia has a long way to go meeting adolescent and youth sexual reproductive health needs. Reproductive Health, 19 (Suppl 1), 130. Amadi, S. O., Udo, S. O., & Chigbu, T. O. (2019). Climate change implications for agricultural sustainability in Enugu in the Guinea Savanna eco-climatic zone of Southeastern Nigeria: Input from climate change proxies. International Journal of Weather, Climate Change and Conservation Research, 5 (1), 1–17. Anikwe, C. C., Mamah, J. E., Okorochukwu, B. C., Nnadozie, U. U., Obarezi, C. H., &Ekwedigwe, K. C. (2020). Age at menarche, menstrual characteristics, and its associated morbidities among secondary school students in Abakaliki, southeast Nigeria. Heliyon, 6 (5). Arthur, A. R. (2023). A systematic review of the predicting factors and barriers to the utilization of antenatal care services in Nigeria: Implications for maternal health and Sustainable Development Goal (SDG) 3. Eberth, J. M., Hung, P., Benavidez, G. A., Probst, J. C., Zahnd, W. E., McNatt, M. K., Toussaint, E., Merrell, M. A., Crouch, E., Oyesode, O. J., & Yell, N. (2022). The problem of the color line: Spatial access to hospital services for minoritized racial and ethnic groups. Health Affairs, 41 (2), 237–246. Ebingha, E. E., Eni, J. S., &Okpa, J. T. (2019). Population growth and socio-economic development of Cross River State, Nigeria. European Journal of Economic and Financial Research. Ezeh, A. N., Enyigwe, J. O., & Egwu, P. N. (2022). Farmers’ utilization of improved rice production technologies in Ebonyi State, Nigeria. Global Journal of Agricultural Sciences, 21 (1), 43–49. Fleming, J., Marvel, S. W., Supak, S., Motsinger-Reif, A. A., & Reif, D. M. (2022). ToxPi* GIS toolkit: Creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS. Journal of Exposure Science & Environmental Epidemiology, 32 (6), 900–907. Gao, J., & O’Neill, B. C. (2020). Mapping global urban land for the 21st century with data-driven simulations and shared socioeconomic pathways. Nature Communications, 11 (1), 2302. Gizaw, Z., Astale, T., & Kassie, G. M. (2022). What improves access to primary healthcare services in rural communities? A systematic review. BMC Primary Care, 23 (1), 313. Guagliardo, M. F. (2004). Spatial accessibility of primary care: Concepts, methods and challenges. International Journal of Health Geographics, 3 (1), 1–13. Gu, D., Andreev, K., & Dupre, M. E. (2021). Major trends in population growth around the world. China CDC Weekly, 3 (28), 604. Haque, M., Islam, T., Rahman, N. A. A., McKimm, J., Abdullah, A., & Dhingra, S. (2020). Strengthening primary health-care services to help prevent and control long-term (chronic) non-communicable diseases in low-and middle-income countries. Risk Management and Healthcare Policy, 409–426. Ike, F., & Esther, N. (2022). Health-care facilities accessibility analysis using GIS: A case study of Uyo Municipal South-Eastern Nigeria. European Journal of Applied Sciences, 10 (1), 313–323. https://doi.org/10.14738/aivp.101.11621 Indicators, A. H. O. (2010). Monitoring the building blocks of health systems. WHO Document Production Services , Geneva, Switzerland. Masoodi, M., & Rahimzadeh, M. (2015). Measuring access to urban health services using geographical information system (GIS): A case study of health service management in Bandar Abbas, Iran. International Journal of Health Policy and Management, 4 (7), 439. Nash, A. (2019). National population projections: 2018-based. Office for National Statistics . Nigeria Population Council (NPC). (2020). Demographic Bulletin 2020 . https://www.nigerianstat.gov.ng/pdfuploads/DEMOGRAPHIC%20BULLETIN%202020.pdf Ninsiima, L. R., Chiumia, I. K., &Ndejjo, R. (2021). Factors influencing access to and utilization of youth-friendly sexual and reproductive health services in sub-Saharan Africa: A systematic review. Reproductive Health, 18 (1), 1–17. Noor, A. M., Amin, A. A., Gething, P. W., Atkinson, P. M., Hay, S. I., & Snow, R. W. (2006). Modelling distances travelled to government health services in Kenya. Tropical Medicine & International Health, 11 (2), 188–196. Nwakamma, M. C., Kenneth, O. I., & Taiwo, O. S. (2024). Challenges of local government in the provision of primary health care services in Ebonyi State, Nigeria. NG Journal of Social Development, 13 (1), 97–116. Obiyan, M., Akinlo, A., &Ogunjuyigbe, P. (2019). Maternal socioeconomic status and fertility behaviour in Nigeria: Evidence from a cross-sectional nationally representative survey. European Scientific Journal. Oliphant, N. P., Ray, N., Bensaid, K., Ouedraogo, A., Gali, A. Y., Habi, O., Maazou, I., Panciera, R., Muñiz, M., Sy, Z., & Manda, S. (2021). Optimising geographical accessibility to primary health care: A geospatial analysis of community health posts and community health workers in Niger. BMJ Global Health, 6 (6), e005238. Onwujekwe, U. G., & Nwali, T. B. (2022). Imperative of development centres for rural development in Ebonyi State: A study of selected centres (2007–2017). Academic Journal of Accounting and Business Management, 3 (3), 37–58. Ouma, P., Macharia, P. M., Okiro, E., &Alegana, V. (2021). Methods of measuring spatial accessibility to health care in Uganda. In Practicing Health Geography: The African Context (pp. 77–90). Cham: Springer International Publishing. Pu, Q., Yoo, E. H., Rothstein, D. H., Cairo, S., &Malemo, L. (2020). Improving the spatial accessibility of healthcare in North Kivu, Democratic Republic of Congo. Applied Geography, 121 , 102262. Rotella, A., Varnum, M. E., Sng, O., & Grossmann, I. (2021). Increasing population densities predict decreasing fertility rates over time: A 174-nation investigation. American Psychologist, 76 (6), 933. Snyder, J. E., Upton, R. D., Hassett, T. C., Lee, H., Nouri, Z., & Dill, M. (2023). Black representation in the primary care physician workforce and its association with population life expectancy and mortality rates in the US. JAMA Network Open, 6 (4), e236687-e236687. Snyman, L., & Coetzee, S. (2024). Measuring geographic accessibility in data-poor rural areas by augmenting the road network with a triangular irregular network–A case study in the OR Tambo District Municipality of the Eastern Cape, South Africa. Journal of Transport Geography, 115 , 103808. World Health Organization. (2019). Report of the global conference on primary health care: From Alma-Ata towards universal health coverage and the Sustainable Development Goals (No. WHO/UHC/IHS/2019.62). World Health Organization . Zhang, P., Ma, W., Wen, F., Liu, L., Yang, L., Song, J., … Liu, Q. (2021). Estimating PM2.5 concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, Ecotoxicology and Environmental Safety, 225 , 112772. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 05 Mar, 2025 Reviews received at journal 04 Mar, 2025 Reviews received at journal 19 Feb, 2025 Reviewers agreed at journal 11 Feb, 2025 Reviews received at journal 11 Feb, 2025 Reviewers agreed at journal 08 Feb, 2025 Reviewers agreed at journal 04 Feb, 2025 Reviewers agreed at journal 02 Feb, 2025 Reviewers agreed at journal 01 Feb, 2025 Reviewers agreed at journal 31 Jan, 2025 Reviewers agreed at journal 30 Jan, 2025 Reviewers agreed at journal 30 Jan, 2025 Reviewers invited by journal 30 Jan, 2025 Editor assigned by journal 30 Jan, 2025 Submission checks completed at journal 29 Jan, 2025 First submitted to journal 03 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5758809","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":397327434,"identity":"9a7806d6-7b4f-44ec-9b6e-c188845a3e1c","order_by":0,"name":"Agatha Arochukwu","email":"","orcid":"","institution":"Agatha Arochukwu National Population Commission","correspondingAuthor":false,"prefix":"","firstName":"Agatha","middleName":"","lastName":"Arochukwu","suffix":""},{"id":397327435,"identity":"c937eade-220e-45e6-a6a0-a6fad31a0def","order_by":1,"name":"Felix Ike","email":"","orcid":"","institution":"Abia State University Uturu","correspondingAuthor":false,"prefix":"","firstName":"Felix","middleName":"","lastName":"Ike","suffix":""},{"id":397327436,"identity":"4f51bc09-184a-4448-82ee-c4346a45d1f2","order_by":2,"name":"Adelowo Adefisayo Adewoyin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACPhCRwGAjxw9mFBChhQ2iJc1YsgHEMCBWCwPD4USDAyCaKC3sPWYSD3ccTjA+vzrxwwMDBnl+sQMEtPCcMZNIPJOeZ3bj7WYJoMMMZ85OIKBFInebRGKbdbHZjbMbQFoSDG4Tp4U5cfOMs5t/kKLFOXEDf+82Im3hOf/ZIrEtzVjiBu82iwQDCcJ+4WdvS7z5sw0Ylf1nN9/8UWEjzy9NQAsQsEiAKQmwSgmCykGA+QPEvgNEqR4Fo2AUjIIRCADuc0JspGqUGgAAAABJRU5ErkJggg==","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":true,"prefix":"","firstName":"Adelowo","middleName":"Adefisayo","lastName":"Adewoyin","suffix":""},{"id":397327440,"identity":"b238475b-043d-4ec3-a538-67fc0bc78308","order_by":3,"name":"Adebayo Eludoyin","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Adebayo","middleName":"","lastName":"Eludoyin","suffix":""}],"badges":[],"createdAt":"2025-01-03 14:08:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5758809/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5758809/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73086836,"identity":"724b1bf1-ee88-4536-96d2-7ff58a0167b5","added_by":"auto","created_at":"2025-01-06 14:56:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":203632,"visible":true,"origin":"","legend":"\u003cp\u003eThe Study Area\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/13901b25c132d2318243e35d.png"},{"id":73086837,"identity":"5db74895-16cc-4eed-a20c-d1db2e1adfba","added_by":"auto","created_at":"2025-01-06 14:56:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":53953,"visible":true,"origin":"","legend":"\u003cp\u003eDriving time to PHCs in different time categories\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/49bbcea8904be6abba29becc.jpg"},{"id":73086841,"identity":"e487f6fc-6561-4cd1-a242-a1f2f10e5f94","added_by":"auto","created_at":"2025-01-06 14:56:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":60281,"visible":true,"origin":"","legend":"\u003cp\u003ePHCsServed and underserved area\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/086795c00ae15e5a0bb9a114.jpg"},{"id":73086851,"identity":"5a849f37-ff5d-4e04-9e19-d1766ef98fed","added_by":"auto","created_at":"2025-01-06 14:56:43","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":63864,"visible":true,"origin":"","legend":"\u003cp\u003eWalking time to PHCs\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/4b5de08b735745ad26202e02.jpg"},{"id":73086848,"identity":"31555ca8-1081-40c6-b099-f186ff2eb1e2","added_by":"auto","created_at":"2025-01-06 14:56:43","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":50670,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of villages per LGA for walking and driving time categories\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/7087fcbaa79ef0c0d97f8d08.jpg"},{"id":73088851,"identity":"1dcb80f4-e276-4d44-8843-0f8ceb296e47","added_by":"auto","created_at":"2025-01-06 15:12:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1420239,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5758809/v1/898f0734-dc11-4b00-bcda-5bfafbc0f1f9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Population Changes and Healthcare Delivery in Ebonyi State, Nigeria","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUnderstanding population growth, health, and resource demands necessitates a comprehensive analysis of demographic dynamics, encompassing the size and composition of the human population over time. Key drivers of population growth include birth rates, death rates, age distribution, fertility, and gender balance (Rotella et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Among these, birth and death rates are particularly critical. Birth rates, measured as births per thousand individuals or females over a specific period, are used to calculate fertility rates the average number of children born over a given time (Nash, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Conversely, death rates provide insights into the impact of human survival on population growth by indicating the rate of deaths within a community over a certain period.\u003c/p\u003e \u003cp\u003eSignificant global demographic shifts are reshaping the demographic environment, particularly in age distribution, growth patterns, and population composition (Gu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Snyder et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Gao \u0026amp; O'Neill (2020) highlight unprecedented variations within and among countries due to global population changes, leading to severe geographical and age-related differences. In more developed countries, fertility and ageing patterns have resulted in older population structures, whereas population growth remains a major concern in developing countries (Atoyebi \u0026amp;Anuodo, 2018). According to Gu et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), the global population is projected to increase from over 7\u0026nbsp;billion in 2011 to over 9\u0026nbsp;billion by 2050, significantly impacting healthcare delivery systems worldwide.\u003c/p\u003e \u003cp\u003eIn Nigeria, rapid population growth has intensified pressure on healthcare services, particularly at the primary healthcare level (Ebingha et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The Nigeria Population Council (NPC, 2020) projected that the population would increase from 188\u0026nbsp;million in 2016 to over 218\u0026nbsp;million by 2022 and beyond. Like many regions in sub-Saharan Africa, Ebonyi State faces challenges related to the unpredictable increase in population and healthcare service quality. Temporal and spatial fluctuations in population size, variation, and socioeconomic characteristics exacerbate these challenges. Urbanization, population growth, and rural-urban migration are significant factors influencing the distribution of healthcare facilities, the need for healthcare services, and resource allocation. The NPC (2020) recorded that Ebonyi State's population is expected to grow at an annual rate of 2.8%, from 2.1\u0026nbsp;million in 2006 to over 3\u0026nbsp;million by 2022. Although total fertility rates (TFRs) in Nigeria have declined gradually from 6.7 in 2008 to 5.3 in 2018, the reduction rate remains high compared to advanced countries (Obiyan et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Population growth in Ebonyi State has significantly impacted healthcare accessibility, marked by high fertility levels and a slight reduction in TFRs. This is particularly prevalent in rural areas where primary health care (PHC) remains the primary point of contact with the health system (Nwakamma et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Gizaw et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) explain that the objective of PHC is to provide community-based, essential, and readily accessible healthcare. The World Health Organization (WHO) Alma-Ata Declaration of 1978 emphasized the importance of PHC in ensuring inclusive healthcare access, especially for marginalized populations (WHO, 2019). Studies support the effectiveness and efficiency of comprehensive PHC systems, which are associated with better healthcare outcomes, lower costs, and fewer hospitalizations for preventable diseases (Haque et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mrejen et al., 2021). Affordable healthcare services and improved quality are consistently linked to robust PHC systems.\u003c/p\u003e \u003cp\u003eDespite significant urban development in Ebonyi State, rural regions still struggle to access adequate healthcare services due to staff shortages, poor transportation networks, and inadequate infrastructure (Onwujekwe\u0026amp; Nwali, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The disparity between rural and urban healthcare facilities is exacerbated by easier access to healthcare services in urban areas. The state has seen a shift towards a younger population structure, with a significant percentage of individuals under 15. This demographic shift has heightened the demand for specialized services such as immunization, reproductive health care, and mental health support (Onwujekwe\u0026amp; Nwali, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The nexus between population dynamics and healthcare delivery is a vital component of public health planning and management. Understanding temporal and spatial population distribution is crucial to ensuring equitable access to healthcare systems. This research aims to determine the dynamics impacting accessible healthcare provision in Ebonyi State, Southeastern Nigeria, and examine the relationship between PHC facility availability, accessibility, and service provision concerning population dynamics.\u003c/p\u003e\n\u003ch3\u003eStudy Area\u003c/h3\u003e\n\u003cp\u003eEbonyi State, created in 1996 from parts of Enugu and Abia States, is located in southeastern Nigeria. It shares borders with Cross River State to the east, Benue State to the north, Enugu State to the west, and Abia State to the south (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). According to the National Population Council (NPC) census of 2006, the population of Ebonyi State was recorded at 2,176,947 (NPC, 2020). Geographically, Ebonyi State lies between latitudes 5\u0026deg; 40' 0\" N and 6\u0026deg; 15' 18\" N and longitudes 7\u0026deg; 40' 55\" E and 8\u0026deg; 05' 55\" E. The state covers a land area of approximately 5,533 km\u0026sup2; within Nigeria's Southeast geopolitical zone (Anikwe et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The state is predominantly inhabited by the Igbo tribe and comprises 13 Local Government Areas (LGAs).\u003c/p\u003e \u003cp\u003eAnnual rainfall in Ebonyi ranges between 1300 mm and 2000 mm, with peak precipitation occurring from July to October. The average daily maximum temperature from January to May fluctuates between 27\u0026deg;C and 35\u0026deg;C (Amadi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The vegetation in Ebonyi State is primarily categorized into three major types: rainforest, tall grass savannah, and woodland. Additionally, the state features freshwater swamps and mangroves in certain areas.\u003c/p\u003e \u003cp\u003eAgriculture is the mainstay of Ebonyi State's economy, with over 85% of the population engaged in agricultural activities. The state produces various cash crops such as oil palm, cashew, cocoa, and rubber. Staple crops include rice (locally branded as Abakaliki rice), yam, cassava, maize, cocoyam, cowpea, and groundnut.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe state also engages in fishing and livestock rearing as primary means of livelihood. The state is rich in natural resources, including salt, zinc, lead, kaolin, limestone, and other minerals, which support small-scale industries and crafts such as blacksmithing and pottery (Ezeh et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n\u003ch2\u003eData collection\u003c/h2\u003e\n\u003cp\u003eA mixed-method approach was employed, incorporating both qualitative and quantitative data collection methods. Data were sourced from both primary and secondary sources. The primary data were collected from PHCs, human resources, medical equipment, and infrastructure through field surveys and GIS methods. The data were obtained using the National Primary Health Care Development Agency's checklist for minimum criteria in PHC delivery in Nigeria (NPHCDA, 1995, 2012). In addition, secondary data were obtained from OpenStreetMap, the Ebonyi State Primary Health Care Development Agency, and the National Population Commission. Additional data, such as road networks, administrative maps, asset lists, and demographic information, were retrieved from the Nigerian Geospatial Data Infrastructure (NGSDI) and fieldwork. Data on facility availability were gathered through physical assessments of infrastructure, staffing, and service delivery compliance with the Minimum Standards Checklist of Primary Health Centers in each of the 171 PHCs in Ebonyi State.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eAnalysis\u003c/h3\u003e\n\u003cp\u003eThe study explored access to healthcare services and the preparedness of PHC facilities in the study area. Data were analyzed using Euclidean distance, Network Analysis, Cost Distance Analysis, and Provider-to-Population Ratio (PPR). Euclidean Distance and Network Analysis were used to analyze distances. Euclidean distance \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\text{e}\\text{q}.\\:1\\right)\\)\u003c/span\u003e\u003c/span\u003eCalculates the straight-line distance between relevant points, such as a residence and the nearest health service site (Guagliardo, \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equa\" class=\"mathdisplay\"\u003e$$\\:d=\\sqrt{{\\left({x}_{2}-{x}_{1}\\right)}^{2}+{\\left({y}_{2}-{y}_{1}\\right)}^{2}}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere \u003cem\u003ed\u003c/em\u003e is the Euclidean distance\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left({x}_{1},\\:{y}_{1}\\right)\\)\u003c/span\u003e\u003c/span\u003eAre the coordinates of the first point, and\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:({x}_{2},\\:{y}_{2})\\)\u003c/span\u003e\u003c/span\u003e Are the coordinates of the second point? Euclidean distance was specifically used to calculate spatial accessibility in rural areas of Ebonyi State, where access to motorized transportation routes is limited (Masoodi \u0026amp; Rahimzadeh, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Noor et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Snyman \u0026amp; Coetzee, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eNetwork analysis \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\left(\\text{e}\\text{q}.\\:2\\right)\\)\u003c/span\u003e\u003c/span\u003eWas used to calculate trip times or distances using real transport routes.\u003c/p\u003e\n\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n\u003cdiv id=\"FileID_Equb\" class=\"mathdisplay\"\u003e$$\\:{T}_{mn}=\\frac{{L}_{m}\\times\\:60}{{S}_{km/h}\\times\\:1000}\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\:\\left(2\\right)$$\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{T}_{mn}\\)\u003c/span\u003e\u003c/span\u003e Is the cost in minutes of travelling over the road or road section, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{L}_{m}\\)\u003c/span\u003e\u003c/span\u003e Is the length of the section in meters, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{S}_{km/h}\\)\u003c/span\u003e\u003c/span\u003e Is the speed limit in km/h (Ouma et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)?\u003c/p\u003e\n\u003cp\u003eIn addition, cost distance analysis calculates journey time, considering variables such as road types, land covers, and elevation. This method provides a means of determining access by developing a cost surface that estimates travel speed on various land cover types (Zhang et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). It is sensitive to spatial resolution and generally works well in Sub-Saharan Africa, where most accessibility decisions are determined by distance (Pu et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). This study generated a cost surface, defining travel speeds within various land covers, roads, and elevations in the study area. This surface was then combined with the spatial distribution of health facilities in a cost-distance analysis to create a surface showing the shortest time needed to get to each health facility for each populated location.\u003c/p\u003e\n\u003cp\u003eThe PPR, also referred to as supply ratios, was computed within bordered areas (Guagliardo, \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). This ratio calculates the accessibility of healthcare by dividing the number of medical facilities, physicians, or beds in an administrative region by the population of that area (Ouma et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). While simple and helpful for identifying service shortages, PPR ignores factors that affect travel, such as elevation, distance, and the availability of transportation (WHO, 2019; Ouma et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, PPR was used to highlight differences between administrative boundaries of health facilities and identify gaps in service delivery.\u003c/p\u003e\n\u003ch3\u003eGIS Analysis\u003c/h3\u003e\n\u003cp\u003eArcGIS by ESRI was utilized as a powerful geographical information system (GIS) tool for advanced mapping and spatial analysis (Fleming et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Geographical accessibility was processed and mapped using the Network Analyst extension add-in, specifically the Service Area (SA) component. Shapefiles and PHC locations projected to the proper coordinate systems ensured accurate spatial distance analysis. This integration allowed for an in-depth evaluation of healthcare accessibility and resource distribution. The Digital Elevation Model (DEM) for Ebonyi State, derived from the Aster GDEM 2011 with a spatial resolution of 30 meters, was used to calculate walking times. The analysis assumed uniform road types across the study area and employed QGIS open-source software (Geospatial Foundation Project, 2015). An administrative map from the National Population Commission defined the study area, representing the division of Ebonyi State into 13 LGAs. Mapping and modelling of the road network dataset, also obtained from the National Population Commission, identified restricted vehicle movement areas. Additional road segments were digitized using Google Earth to address topological problems in the dataset. The improved road network and PHC facility locations were then assessed using ArcGIS software to enhance the precision of spatial modelling. This methodology enabled an accurate assessment of PHC facility accessibility, considering topography and infrastructure limitations.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePopulation changes\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the population distribution across the 13 Local Government Areas (LGAs) of Ebonyi State as of 2022, detailing the trends in gender distribution and the percentage contribution of each LGA to the state's total population. The most populous LGAs are Izzi, Onicha, Ikwo, and Ohaukwu, each with an approximate population of 300,000. Specifically, Izzi LGA has the largest proportion, accounting for approximately 13.8% of the state's population, followed by Ikwo and Onicha with 11.5% and 9.2%, respectively. In contrast, Ivo LGA has a population of 188,789, contributing 4.6% to the state's total population. These population discrepancies highlight the need for targeted healthcare interventions, particularly due to the demographic differences between densely and sparsely populated areas.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimated population distribution by gender within the local government areas in Ebonyi State as of2022\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRatio of total male (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRatio of total female (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e% distribution across LGA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbakaliki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e112807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e120036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e227345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e104615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIkwo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e334400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e155332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e179068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIshielu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e237351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e113045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e124306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e188789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIzzi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e192653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaozara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e230718\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e113905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaukwu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e304200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e146969\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e157231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnicha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e184766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe population of Ebonyi State is fairly balanced, with 51% females and 49% males. However, within each Local Government Area (LGA), this varies significantly. For instance, Izzi and Ikwo LGAs have a much higher proportion of females, while Afikpo South has a more balanced gender distribution. The demographic diversity across the state is also reflected in the proportion of each LGA's contribution to the state's total population. As the most populous LGA, Izzi contributes 13.8% to the total population, whereas Ivo, the least populous, accounts for only 4.6%. Ebonyi LGA lies in the middle of the state's population distribution, accounting for 9.1% of the total population.\u003c/p\u003e \u003cp\u003eThese variations indicate different health requirements across LGAs. Densely populated areas necessitate more medical equipment, personnel, and healthcare facilities to meet the growing demand for services. In Ivo LGA, the gender ratio is relatively balanced, with 41% men and 40% women. However, the significant disparity in the number of females to males in LGAs such as Izzi and Ikwo could be attributed to regional variations in fertility rates, migration, or other socioeconomic factors.\u003c/p\u003e \u003cp\u003eThese population trends have significant healthcare implications. LGAs like Izzi and Ikwo, with increasing populations, require more healthcare services, including larger facilities, more staff, and additional medical supplies. The higher proportion of females in these areas necessitates an increased focus on maternity, reproductive, and family planning services. Additionally, pediatric care, vaccination campaigns, and other preventive healthcare measures must be prioritized, given the young population in many LGAs.\u003c/p\u003e \u003cp\u003eAlthough the elderly make up only about 5% of the population, they cannot be overlooked, especially as the population ages and grows. The uneven population distribution in Ebonyi State leads to higher healthcare costs in densely populated areas such as Izzi and Ikwo. Changes in gender distribution highlight the need for tailored health services for men and women based on their specific needs. Effective health planning and resource allocation are crucial to ensure that, as the population of Ebonyi State increases, all residents, particularly those in high-density areas, receive appropriate healthcare services.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDistribution by gender\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the percentage distribution of the population by sex ratio across the 13 Local Government Areas (LGAs) in the study area. Notably, 71% of the LGAs have an even distribution of males and females. Izzi and Onicha LGAs stand out with the highest percentages of male and female residents, each accounting for 11% of their respective totals, indicating high population densities. Ohaukwu and Ikwo LGAs also show significant population concentrations, with Ohaukwu accounting for 9% of the male population and Ikwo contributing between 8\u0026ndash;10% of the total population. In contrast, Ivo LGA is the least densely populated area, comprising only 6% males and 5% females. The overall gender mix in Ebonyi State is predominantly female, with a male-to-female ratio of 49\u0026ndash;51%. This balanced gender distribution underscores the state's stable population dynamics and has important implications for planning and implementing equitable policies and resource allocations. For example, densely populated LGAs like Izzi and Onicha may need to prioritize healthcare and social services to cater to their larger populations. Additionally, the higher proportion of females in these areas suggests a greater need for maternity, reproductive, and family planning services. Ensuring the appropriate allocation of medical equipment, personnel, and facilities in these LGAs is crucial to meeting the healthcare demands of their residents.\u003c/p\u003e \u003cp\u003eIn summary, understanding the demographic characteristics of Ebonyi State, particularly the population distribution and gender ratios, is essential for effective healthcare planning and resource allocation. This approach will help address the varying health needs across different LGAs, ensuring equitable access to healthcare services for all residents.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage distribution of the population by gender across the State\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRatio of total male (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRatio of total female (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbakaliki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1128067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e120036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e227345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e104615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e175519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e192653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIkwo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e183296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e184766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIshielu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e232843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1128067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e120036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIzzi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e123035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaozara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaukwu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e227345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109420\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e117925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnicha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e103248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e104615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eDistribution by age group\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the percentage distribution of the Ebonyi State population by age group, revealing significant demographic trends. The population is predominantly young, with over 51% under 20 years old. There is substantial workforce potential, as 44% of the population is within the prime working age of 20 to 59 years. The elderly population, those over 60 years old, constitutes only 5%, indicating a relatively small proportion. The data illustrate that the population gradually decreases with increasing age, with younger age groups significantly larger compared to older ones. Interestingly, there are more women than men in the older age groups, while men dominate the population under 20 years old. This has important implications for education, employment, and health planning, particularly in areas such as maternity and child health and support for the ageing population. The demographic composition is consistent with trends in sub-Saharan Africa, where populations tend to be younger. Approximately 5% of the population is 60 or older, highlighting the growing need for healthcare services for an ageing population in the coming decades. Additionally, the significant proportion of younger individuals suggests a greater demand for maternal and paediatric care services.\u003c/p\u003e \u003cp\u003eUnderstanding these demographic characteristics is crucial for effective healthcare planning. The young demographic composition of Ebonyi State underscores the necessity for targeted health interventions and resource allocations to meet the diverse needs of its population. This approach will ensure that, as the population grows, particularly in younger and ageing segments, all residents receive the appropriate healthcare services.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage Distribution by Age Group\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%Male\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%Female\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%Total\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e445670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e215324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e211050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e426374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e208222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e205602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e413824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e186703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e189164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e375867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e132647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e272230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e211780\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e6.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e99375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e183478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e171753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e151479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e133285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e99624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e66044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e75\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10819\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5668\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6494\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAccessibility to Primary Health Care Facilities\u003c/h2\u003e \u003cp\u003eThe study on accessibility to primary health care (PHC) facilities revealed that 81.1% of villages in Ebonyi State could reach a PHC within 60 minutes, and 63.1% of villages are within a 10-minute driving distance, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Conversely, 18.9% of communities are considered underserved, lying outside the 60-minute travel criterion, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Accessibility varies significantly across different Local Government Areas (LGAs). LGAs such as Ishielu, Izzi, Afikpo North, and Afikpo South face challenges in accessibility due to inadequate road infrastructure and longer travel distances. In contrast, LGAs such as Abakaliki, Ebonyi, Ezza North, and Ohaukwu have the majority of locations fully accessible to PHCs by car.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis disparity underscores the need for targeted interventions to improve road infrastructure and reduce travel time to healthcare facilities in underserved areas. Enhancing accessibility to PHCs is crucial for ensuring equitable healthcare delivery and meeting the health needs of all residents in Ebonyi State. Addressing these accessibility issues will involve strategic planning and investment in infrastructure development, particularly in LGAs with poor access to healthcare services. This approach will contribute to the overall improvement of healthcare outcomes and the well-being of the population in Ebonyi State.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWalking and Driving Scenarios for Underserved and Served Areas\u003c/h2\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e compare walking and driving scenarios for underserved and served areas. While driving offers quicker access, a significant portion of the rural population still relies on walking as their primary mode of transportation due to the scarcity of motorized vehicles. The maps illustrate that underserved areas are more readily identifiable on foot, although, in some regions, it can take over an hour to walk to a primary healthcare centre (PHC). Notably, this includes villages in Izzi, Ishielu, and parts of Ohaukwu. These findings highlight the need for strategic interventions to improve accessibility, such as enhancing transportation infrastructure and increasing the availability of motorized transport in rural areas. Ensuring that all residents can access healthcare services within a reasonable timeframe is crucial for the overall health and well-being of the population in Ebonyi State.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFor the walking scenario (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), using the same time intervals as in the driving scenario, it was found that approximately 42.1% of the villages are located within a 10-minute walk from PHCs. This percentage decreases significantly to 21.0% for villages within a 50-minute walking distance. Overall, 63.1% of the population can reach a PHC within a 60-minute walk. However, 37.9% of the villages typically require more than 60 minutes to walk to a PHC, indicating that these villages are underserved. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the service area for walking time to PHCs in Ebonyi State.These findings emphasize the need for targeted interventions to improve accessibility, such as developing transportation infrastructure and increasing the availability of motorized transport in rural areas. Ensuring that all residents can access healthcare services within a reasonable timeframe is crucial for the overall health and well-being of the population in Ebonyi State.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eComparison with the Minimum Standard Checklist for PHCs\u003c/h2\u003e \u003cp\u003eThe assessment of the spatial distribution and adequacy of public health facilities across Ebonyi State reveals significant disparities in the delivery of primary health care (PHC) services. Health planners aim to ensure that administrative units are equipped with the necessary number of public health facilities and adequate resources, including physical infrastructure, human resources, and medical care for the community served.\u003c/p\u003e \u003cp\u003eIn the study area, Ikwo LGA has a total of 20 PHC facilities, making it the largest in Ebonyi State, followed by Ishielu with 16 facilities. Izzi has thirteen, while Abakaliki and Ohaukwu each have fifteen facilities. Other LGAs, including Afikpo North, Ebonyi, and Onicha, also have PHC facilities. However, LGAs such as Ohaozara, Ivo, Ezza South, Ezza North, and Afikpo South each have 11 facilities. This distribution indicates that many regions are inadequately equipped with primary health facilities and health-related human resources, resulting in uneven coverage and accessibility issues.\u003c/p\u003e \u003cp\u003eThe number of PHC facilities and Human Resources for Health (HRH) per 10,000 population is a standardized metric for measuring the accessibility of healthcare services. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, several LGAs have less than one PHC facility per 10,000 population, indicating poor service coverage. For example, Ebonyi and Abakaliki LGAs have 0.8 PHC facilities per 10,000 population, compared to 0.7 in Ishielu and Ezza North. HRH is remarkably scarce throughout the state; only a few LGAs have one health worker per 10,000 residents. Ebonyi, Afikpo South, and Ikwo are among the LGAs with the lowest ratios of 0.1, while Ezza North has the highest ratio at 0.2 per 10,000. This deficiency highlights the urgent need to increase the number of PHCs and HRHs to meet the population's health demands.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePHC facilities and HRH per 10,000 population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLga\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Sampled PHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePHC Pop\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage PHC/ 10,000 Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAverage HRH/ 10,000 Population\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbakaliki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e185679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e142055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e143588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIkwo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIshielu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e207077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e102163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIzzi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e116754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaozara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e127214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaukwu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e125382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnicha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAvailability of Medical Equipment and Physical Infrastructure in PHCs\u003c/h2\u003e \u003cp\u003eThe availability of medical equipment and physical infrastructure in primary healthcare centers (PHCs) is crucial for effective service delivery. Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e indicates that the availability of medical equipment across all Local Government Areas (LGAs) is less than 50%. Afikpo North has the highest proportion of available medical equipment at 37.6%, while Onicha has the lowest at 30.7%. The availability of physical infrastructure also varies significantly, with Izzi at 51.7% and Ebonyi at 41.3%. These deficiencies highlight a general lack of resources needed to provide quality primary health services.When comparing the availability of medical equipment, Ebonyi South is relatively higher compared to Ebonyi North and Ebonyi Central, with proportions of 34.0%, 30.0%, and 33.6%, respectively. For physical infrastructure, Ebonyi Central accounts for 43.8%, Ebonyi North 44.0%, and Ebonyi South 40.8%. Despite these regional differences, the overall availability of resources remains below the minimum standards required for effective healthcare delivery.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePHC Service Readiness\u003c/h2\u003e \u003cp\u003eThe provision of quality healthcare depends on the readiness of services, which includes facilities, tools, and personnel. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates that PHC facilities across LGAs vary in their capacity to serve their estimated populations. For instance, Ezza North serves 131% of its predicted population, indicating an overstretched facility, whereas Ikwo serves only 57% of its population, signifying underutilization.Human resources for health (HRH) are remarkably scarce throughout the state, with availability ranging from 15% in Ezza North to as low as 6% in Ikwo. The availability of medical equipment also varies, from 30.7% in Onicha to 37.6% in Afikpo North, which is inadequate. The inadequacy of resources is further demonstrated by the availability of physical infrastructure, with Izzi having the highest at 50.1%, while Afikpo South has the lowest at 41%.These disparities in healthcare access and resource availability highlight the urgent need to increase the number of PHCs and HRHs to meet the health demands of the population. Addressing these gaps will ensure more equitable healthcare access and improve the overall efficiency of healthcare delivery in Ebonyi State.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAvailability of Medical Equipment and Physical Infrastructure in PHCs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMedical Equipment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003ePhysical Infrastructure\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRequired\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e% Available\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRequired\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbakaliki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIkwo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIshielu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIzzi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e50.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaozara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaukwu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnicha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePHC Service Readiness in Ebonyi State by LGA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003ePHC Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eHuman Resources\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eMedical Equipment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003ePhysical Infrastructure\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSampled PHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRequired Population (\u0026lsquo;000)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e% of Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRequired\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e% Available\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRequired\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e%\u003c/p\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eRequired\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eAvailable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e% Available\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpoNorth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e80391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e37.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfikpo South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e96614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIvo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e102163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e46.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaozara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e127214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnicha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e48.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAbakaliki\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e185679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEbonyi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e142055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e32.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIzzi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e116754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1685\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e50.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOhaukwu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e125382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e5655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e33.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e143588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzza South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e70772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e4147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e42.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIkwo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e7540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2582\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e34.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIshielu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e207077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e6032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e43.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study comprehensively examines the spatial accessibility, resource availability, and service preparedness of primary healthcare (PHC) institutions in Ebonyi State, Nigeria, highlighting significant gaps in the pursuit of equitable healthcare. It reveals marked disparities in the distribution of PHC facilities, staff, medical supplies, and physical infrastructure, reflecting broader systemic obstacles to achieving Universal Health Coverage (UHC).The spatial accessibility analysis demonstrated that most Local Government Areas (LGAs) fell below the threshold of having one PHC facility per 10,000 people, although certain LGAs, such as Ikwo and Ohaukwu, have higher ratios. These disparities, particularly pronounced between the northern and central zones, underscore the unequal distribution of healthcare resources in underprivileged areas. This finding is consistent with international research indicating that geographic proximity to health facilities can improve health outcomes and utilization rates (WHO, 2019).\u003c/p\u003e \u003cp\u003eThe study highlights a severe shortage of human resources for health, with most LGAs reporting less than one health worker per 10,000 inhabitants. Additionally, the average availability of medical equipment across the state is less than 50%, compounded by inadequate physical infrastructure. These deficiencies are particularly acute in Ebonyi North and Central Senatorial Districts, which have dense populations further straining the limited available resources. This pattern aligns with national trends in Nigeria, where chronic underinvestment in health staffing and facilities disproportionately affects rural areas, exacerbating health disparities.\u003c/p\u003e \u003cp\u003eDisparities in service readiness and resource distribution also reflect systemic inefficiencies in health planning and governance. For example, the very low utilization rates of PHC facilities in LGAs such as Ikwo contrast sharply with overcrowding in LGAs such as Ezza North and Abakaliki, where population coverage exceeds 120%. This underscores the need for a more strategic, data-driven approach to resource distribution, considering geography and population dynamics in health policy decisions. Strengthening PHC systems to enhance service readiness is crucial, as shortages in amenities, diagnostic equipment, and human resources hinder the ability of PHC facilities to offer comprehensive services. These deficits also undermine the state's capacity to respond effectively to emergencies, posing challenges to achieving UHC by 2030 (Arthur, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study further establishes that health service delivery interacts with population dynamics. The high population growth rates and preponderance of young people in Ebonyi State drive increasing demand for maternity and child health services, as well as interventions for both communicable and non-communicable diseases. Addressing these challenges requires increased hiring and training of healthcare professionals, adequate medical equipment, and sustained investments in PHC infrastructure.\u003c/p\u003e \u003cp\u003eComparing these findings with those from other African countries and the Western world reveals both convergences and divergences. The 2.8% annual population growth rate in Ebonyi aligns with the general trend in Sub-Saharan Africa, characterized by rapidly growing populations that strain health systems (Gu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Adeleye et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In contrast, Western countries face slower population growth and aging populations. Urbanization and high fertility rates in Ebonyi outpace infrastructure development, creating additional challenges. Gender dynamics in Ebonyi, similar to other African countries like South Africa and Ethiopia, show higher healthcare needs for women due to reproductive health issues (Ninsiima et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Admassu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mbachu et al., 2022). In the West, research focuses more on mental health disparities, such as the higher prevalence of depression among females, which can be more effectively treated due to better access to healthcare services.\u003c/p\u003e \u003cp\u003eRegarding healthcare accessibility, 81.1% of the population in Ebonyi State can access PHCs within a 60-minute travel time, similar to Kenya (Oliphant et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, disadvantaged districts remain, highlighting the need for targeted interventions. While access to healthcare is also a challenge in some Western areas, such as Appalachia, these regions often have better infrastructure compared to rural areas in Ebonyi (Eberth et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn all, the study underscores critical gaps in healthcare resource provision, including poor provider-to-population ratios and insufficient medical equipment. Western countries like Canada and Germany benefit from better resource distribution and robust healthcare infrastructure, as noted by Marchildon et al. (2022). These comparisons illustrate the urgent need for Ebonyi State to address its rapidly expanding population and resource shortages through improved healthcare policies and facilities.\u003c/p\u003e "},{"header":"Conclusion and Recommendations","content":"\u003cp\u003eThis study establishes that PHC facilities across Ebonyi State, Nigeria, are grossly unequal in their spatial accessibility, resource availability, and service readiness. The inequitable distribution of PHC buildings, personnel, medical supplies, and physical infrastructure indicates structural inefficiencies that hinder equitable healthcare provision. While some LGAs, such as Ikwo and Ohaukwu, have relatively good facility-to-population ratios, many LGAs fall below the minimum threshold. Additionally, gaps in facility distribution are particularly evident in the northern and central senatorial zones, exacerbated by high population density and inadequate healthcare infrastructure.\u003c/p\u003e\u003cp\u003eThe study also reveals significant deficiencies in basic amenities and diagnostic equipment, compounded by low human resources-population ratios, which impair the capacity of PHCs to provide comprehensive care. While some PHC facilities are underutilized, others exceed their prescribed capacity, indicating the need for a more systematic and information-driven approach to health planning and budgeting.\u003c/p\u003e\u003cp\u003eAddressing these gaps requires specific funding for PHC infrastructure, equitable resource distribution, and the recruitment and training of medical personnel. Incorporating population dynamics into health policy formulation will ensure that service delivery meets the needs of all areas, particularly disadvantaged ones. Strengthening the PHC system in Ebonyi State is essential to achieving health equity and universal health coverage. Prioritizing poor areas and adhering to equity principles in health planning will ensure access to essential health services for all citizens, promote sustainable development, and assure health equality.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the participants in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for the study was obtained from the Ebonyi State Health Research Ethics Committee. \u0026nbsp;All respondents granted their verbal informed consent, and where required interpretations have been provided to ensure understanding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project is a self-funding project\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor notes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAgatha Arochukwu, is the first author, with Felix Ike, Adelowo Adefisayo Adewoyin, \u0026amp;\u003csup\u003e\u0026nbsp;\u003c/sup\u003eAdebayo Eludoyin as corresponding authors and contributed equally to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFelix Ike and Agatha Arochukwu conceptualized the research. Agatha Arochukwu collects the primary data for this research. Adelowo Adefisayo Adewoyin drafted the manuscript. \u0026nbsp;Felix Ike and Adebayo Eludoyin performed software and method validation. \u0026nbsp;All authors re-reviewed and co-revised the manuscript from the English language perspective. \u0026nbsp;All authors made significant intellectual contributions to multiple revisions of the draft. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAgatha Arochukwu,\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003e\u003cu\[email protected]\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIke Felix,\u0026nbsp;\u003c/strong\u003e\u003cu\[email protected]\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdewoyin A.A,\u0026nbsp;\u003c/strong\[email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eO. A. Eludoyin\u003c/strong\u003e, [email protected]\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eEthical approval for the study was obtained from the Ebonyi State Health Research Ethics Committee. \u0026nbsp;All respondents granted their verbal informed consent, and where required interpretations have been provided to ensure understanding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeleye, O., Adebowale, A., Adeyemo, O., Adeoye, I., Afolabi, R., Fagbamigbe, A., \u0026amp;Palamuleni, M. (2023). Decomposition and spatiotemporal analysis of barriers to healthcare access among women of childbearing age in Nigeria, using Nigeria Demographic and Health Survey from 2003 to 2018. \u003cem\u003eJournal of African Population Studies\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdmassu, T. W., Wolde, Y. T., \u0026amp; Kaba, M. (2022). Ethiopia has a long way to go meeting adolescent and youth sexual reproductive health needs. Reproductive Health, \u003cem\u003e19\u003c/em\u003e(Suppl 1), 130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmadi, S. O., Udo, S. O., \u0026amp; Chigbu, T. O. (2019). Climate change implications for agricultural sustainability in Enugu in the Guinea Savanna eco-climatic zone of Southeastern Nigeria: Input from climate change proxies. International Journal of Weather, Climate Change and Conservation Research, \u003cem\u003e5\u003c/em\u003e(1), 1\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnikwe, C. C., Mamah, J. E., Okorochukwu, B. C., Nnadozie, U. U., Obarezi, C. H., \u0026amp;Ekwedigwe, K. C. (2020). Age at menarche, menstrual characteristics, and its associated morbidities among secondary school students in Abakaliki, southeast Nigeria. Heliyon, \u003cem\u003e6\u003c/em\u003e(5).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArthur, A. R. (2023). A systematic review of the predicting factors and barriers to the utilization of antenatal care services in Nigeria: Implications for maternal health and Sustainable Development Goal (SDG) 3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEberth, J. M., Hung, P., Benavidez, G. A., Probst, J. C., Zahnd, W. E., McNatt, M. K., Toussaint, E., Merrell, M. A., Crouch, E., Oyesode, O. J., \u0026amp; Yell, N. (2022). The problem of the color line: Spatial access to hospital services for minoritized racial and ethnic groups. Health Affairs, \u003cem\u003e41\u003c/em\u003e(2), 237\u0026ndash;246.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEbingha, E. E., Eni, J. S., \u0026amp;Okpa, J. T. (2019). Population growth and socio-economic development of Cross River State, Nigeria. European Journal of Economic and Financial Research.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEzeh, A. N., Enyigwe, J. O., \u0026amp; Egwu, P. N. (2022). Farmers\u0026rsquo; utilization of improved rice production technologies in Ebonyi State, Nigeria. Global Journal of Agricultural Sciences, \u003cem\u003e21\u003c/em\u003e(1), 43\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleming, J., Marvel, S. W., Supak, S., Motsinger-Reif, A. A., \u0026amp; Reif, D. M. (2022). ToxPi* GIS toolkit: Creating, viewing, and sharing integrative visualizations for geospatial data using ArcGIS. Journal of Exposure Science \u0026amp; Environmental Epidemiology, \u003cem\u003e32\u003c/em\u003e(6), 900\u0026ndash;907.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao, J., \u0026amp; O\u0026rsquo;Neill, B. C. (2020). Mapping global urban land for the 21st century with data-driven simulations and shared socioeconomic pathways. Nature Communications, \u003cem\u003e11\u003c/em\u003e(1), 2302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGizaw, Z., Astale, T., \u0026amp; Kassie, G. M. (2022). What improves access to primary healthcare services in rural communities? A systematic review. BMC Primary Care, \u003cem\u003e23\u003c/em\u003e(1), 313.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuagliardo, M. F. (2004). Spatial accessibility of primary care: Concepts, methods and challenges. International Journal of Health Geographics, \u003cem\u003e3\u003c/em\u003e(1), 1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu, D., Andreev, K., \u0026amp; Dupre, M. E. (2021). Major trends in population growth around the world. China CDC Weekly, \u003cem\u003e3\u003c/em\u003e(28), 604.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaque, M., Islam, T., Rahman, N. A. A., McKimm, J., Abdullah, A., \u0026amp; Dhingra, S. (2020). Strengthening primary health-care services to help prevent and control long-term (chronic) non-communicable diseases in low-and middle-income countries. Risk Management and Healthcare Policy, 409\u0026ndash;426.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIke, F., \u0026amp; Esther, N. (2022). Health-care facilities accessibility analysis using GIS: A case study of Uyo Municipal South-Eastern Nigeria. European Journal of Applied Sciences, \u003cem\u003e10\u003c/em\u003e(1), 313\u0026ndash;323. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14738/aivp.101.11621\u003c/span\u003e\u003cspan address=\"10.14738/aivp.101.11621\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIndicators, A. H. O. (2010). Monitoring the building blocks of health systems. \u003cem\u003eWHO Document Production Services\u003c/em\u003e, Geneva, Switzerland.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasoodi, M., \u0026amp; Rahimzadeh, M. (2015). Measuring access to urban health services using geographical information system (GIS): A case study of health service management in Bandar Abbas, Iran. International Journal of Health Policy and Management, \u003cem\u003e4\u003c/em\u003e(7), 439.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNash, A. (2019). National population projections: 2018-based. \u003cem\u003eOffice for National Statistics\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNigeria Population Council (NPC). (2020). \u003cem\u003eDemographic Bulletin 2020\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nigerianstat.gov.ng/pdfuploads/DEMOGRAPHIC%20BULLETIN%202020.pdf\u003c/span\u003e\u003cspan address=\"https://www.nigerianstat.gov.ng/pdfuploads/DEMOGRAPHIC%20BULLETIN%202020.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNinsiima, L. R., Chiumia, I. K., \u0026amp;Ndejjo, R. (2021). Factors influencing access to and utilization of youth-friendly sexual and reproductive health services in sub-Saharan Africa: A systematic review. Reproductive Health, \u003cem\u003e18\u003c/em\u003e(1), 1\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoor, A. M., Amin, A. A., Gething, P. W., Atkinson, P. M., Hay, S. I., \u0026amp; Snow, R. W. (2006). Modelling distances travelled to government health services in Kenya. Tropical Medicine \u0026amp; International Health, \u003cem\u003e11\u003c/em\u003e(2), 188\u0026ndash;196.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNwakamma, M. C., Kenneth, O. I., \u0026amp; Taiwo, O. S. (2024). Challenges of local government in the provision of primary health care services in Ebonyi State, Nigeria. NG Journal of Social Development, \u003cem\u003e13\u003c/em\u003e(1), 97\u0026ndash;116.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObiyan, M., Akinlo, A., \u0026amp;Ogunjuyigbe, P. (2019). Maternal socioeconomic status and fertility behaviour in Nigeria: Evidence from a cross-sectional nationally representative survey. European Scientific Journal.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOliphant, N. P., Ray, N., Bensaid, K., Ouedraogo, A., Gali, A. Y., Habi, O., Maazou, I., Panciera, R., Mu\u0026ntilde;iz, M., Sy, Z., \u0026amp; Manda, S. (2021). Optimising geographical accessibility to primary health care: A geospatial analysis of community health posts and community health workers in Niger. BMJ Global Health, \u003cem\u003e6\u003c/em\u003e(6), e005238.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnwujekwe, U. G., \u0026amp; Nwali, T. B. (2022). Imperative of development centres for rural development in Ebonyi State: A study of selected centres (2007\u0026ndash;2017). Academic Journal of Accounting and Business Management, \u003cem\u003e3\u003c/em\u003e(3), 37\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOuma, P., Macharia, P. M., Okiro, E., \u0026amp;Alegana, V. (2021). Methods of measuring spatial accessibility to health care in Uganda. In \u003cem\u003ePracticing Health Geography: The African Context\u003c/em\u003e (pp. 77\u0026ndash;90). Cham: Springer International Publishing.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePu, Q., Yoo, E. H., Rothstein, D. H., Cairo, S., \u0026amp;Malemo, L. (2020). Improving the spatial accessibility of healthcare in North Kivu, Democratic Republic of Congo. Applied Geography, \u003cem\u003e121\u003c/em\u003e, 102262.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRotella, A., Varnum, M. E., Sng, O., \u0026amp; Grossmann, I. (2021). Increasing population densities predict decreasing fertility rates over time: A 174-nation investigation. American Psychologist, \u003cem\u003e76\u003c/em\u003e(6), 933.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnyder, J. E., Upton, R. D., Hassett, T. C., Lee, H., Nouri, Z., \u0026amp; Dill, M. (2023). Black representation in the primary care physician workforce and its association with population life expectancy and mortality rates in the US. JAMA Network Open, \u003cem\u003e6\u003c/em\u003e(4), e236687-e236687.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnyman, L., \u0026amp; Coetzee, S. (2024). Measuring geographic accessibility in data-poor rural areas by augmenting the road network with a triangular irregular network\u0026ndash;A case study in the OR Tambo District Municipality of the Eastern Cape, South Africa. Journal of Transport Geography, \u003cem\u003e115\u003c/em\u003e, 103808.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. (2019). Report of the global conference on primary health care: From Alma-Ata towards universal health coverage and the Sustainable Development Goals (No. WHO/UHC/IHS/2019.62). \u003cem\u003eWorld Health Organization\u003c/em\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, P., Ma, W., Wen, F., Liu, L., Yang, L., Song, J., \u0026hellip; Liu, Q. (2021). Estimating PM2.5 concentration using the machine learning GA-SVM method to improve the land use regression model in Shaanxi, Ecotoxicology and Environmental Safety, \u003cem\u003e225\u003c/em\u003e, 112772.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dihs","sideBox":"Learn more about [Discover Health Systems](https://www.springer.com/44250)","snPcode":"44250","submissionUrl":"https://submission.nature.com/new-submission/44250/3","title":"Discover Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Population dynamics, GIS analysis, healthcare accessibility, Ebonyi State, spatial distribution","lastPublishedDoi":"10.21203/rs.3.rs-5758809/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5758809/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the population dynamics of healthcare delivery in Ebonyi State, Nigeria, emphasising gender disparities, spatial distribution, and the accessibility of basic health facilities, employing Geographic Information Systems (GIS) for analysis. The research reveals that Izzi, Onicha, Ikwo, and Ohaukwu Local Government Areas (LGAs) collectively account for over 40% of the state's population. Demographic data indicates a 2.8% annual population growth across the 13 LGAs from 2006 to 2022, with Ivo LGA, the least populated, representing approximately 4.6% of the state's population. The GIS analysis indicates that 81.1% of the population resides within 60 minutes of a primary healthcare centre (PHC), though accessibility varies significantly, especially in rural areas. The gender distribution shows an overall balance with 49% males and 51% females; however, LGAs such as Izzi and Ikwo exhibit a higher proportion of females than males. These findings underscore the necessity for targeted healthcare interventions, including equitable resource allocation, enhancement of PHC facilities, and the provision of gender-sensitive services such as maternity and pediatric care. The GIS-based accessibility mapping highlights the importance of incorporating spatial analysis into healthcare planning to identify underserved areas and optimise resource allocation. This study provides essential data for developing population-centered, spatially aware, and sustainable healthcare policies in Ebonyi State, thus serving as a valuable resource for international health researchers and policymakers.\u003c/p\u003e","manuscriptTitle":"Population Changes and Healthcare Delivery in Ebonyi State, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-06 14:56:37","doi":"10.21203/rs.3.rs-5758809/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-06T04:52:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-04T13:38:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-19T10:16:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"272378793605271522157737257953438103767","date":"2025-02-11T15:10:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-11T09:57:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"208374610406631838533803371737868604552","date":"2025-02-08T20:00:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267942988568376136893206918369507191332","date":"2025-02-05T02:54:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247212991514232707706369223942891457151","date":"2025-02-02T19:06:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160470748836146581124734253994458731427","date":"2025-02-02T04:40:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87035041398382608029899646924934467440","date":"2025-01-31T14:41:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1906462943491052105983369093815636296","date":"2025-01-30T14:03:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166007486609471603838697151906134873056","date":"2025-01-30T11:11:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-30T10:40:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-30T05:35:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-01-29T06:21:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Health Systems","date":"2025-01-03T14:04:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-health-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dihs","sideBox":"Learn more about [Discover Health Systems](https://www.springer.com/44250)","snPcode":"44250","submissionUrl":"https://submission.nature.com/new-submission/44250/3","title":"Discover Health Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14091ca8-3499-4146-83ba-a95a0959e7c5","owner":[],"postedDate":"January 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-05-08T10:23:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-06 14:56:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5758809","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5758809","identity":"rs-5758809","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}