Timeliness of Malaria Treatment in Children Under Five Years in Uganda: An Analysis of 2016 Demographic Health Survey Data

Timeliness of Malaria Treatment in Children Under Five Years in Uganda: An Analysis of 2016 Demographic Health Survey Data | 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 Timeliness of Malaria Treatment in Children Under Five Years in Uganda: An Analysis of 2016 Demographic Health Survey Data John Bosco Asiimwe, Eriot Kadubira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4726273/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Malaria is ranked among the major causes of morbidity and mortality in children under 5 years of age in Uganda. Prompt and early appropriate malaria treatment can prevent progression of illness to severe stages, thereby mitigating mortality and morbidity. Therefore, this study aimed at determining the factors associated with timeliness to malaria treatment in children under five years in Uganda. Method: This study used 2016 Uganda Demographic and Health Survey data and a total of 4,063 children under age of five years who had fever as a proxy for malaria two weeks prior to the survey were included. The median time to malaria treatment using Kaplan Meier curve were computed. A multivariable Cox regression model were fitted to establish factors associated with time to malaria treatment. Proportional hazard assumption was checked graphically and using Schoenfeld residual statistical test. Results: Forty one percent of the children delayed to receive prompt malaria treatment beyond the recommended 24 hours. The median time to malaria treatment was 24 hours after onset of malaria symptoms. Children whose mothers made decisions jointly as a wife and a spouse on treatment were associated with faster time to malaria treatment (HR=1.11, 95%CI: 1.02-1.21) compared to when the mother made decisions alone. Children whose mothers sought treatment from community health workers were associated with faster time to malaria treatment (HR=1.17, 95%CI: 1.02-1.34) compared to those who did not. Children whose mothers/caregivers were from Western region (HR=0.84, 95%CI: 0.73-0.96) of the country were associated with delayed time to malaria treatment compared to other regions of the country. Similarly, children whose mothers frequently listened to radio were significantly associated with faster time (HR=1.11, 95%CI: 1.02-1.21) to treatment of malaria compared to those who did not listen to radio. Conclusion: Faster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region of Uganda and frequency of listening to radio. Thus malaria control initiatives should focus its strategy on strengthening health interventions through introduction of programmes that can empower joint spousal decision making capabilities, facilitations and equipping of community health workers with malaria treatment, and increased frequent use of radios to relay malaria messages to communities. Health Policy Malaria treatment Uganda time mothers Introduction Malaria is ranked among the diseases that have contributed greatly to the death of many children and adults worldwide( 1 ). Globally about 438,000 deaths caused by malaria were recorded in 2015, 90% of these deaths occurred in Sub Saharan Africa and almost 71% of the deaths were for children under five years ( 2 ). Malaria accounts for about 10% of all death among under 5 children in Sub Saharan Africa. Uganda has made great strides in curbing malaria prevalence from 42% in 2009 to 9% in 2018( 3 ). Despite all the interventions to reduce malaria transmissions like the distribution of free insecticide-treated nets and indoor residual spraying in a limited number of districts where malaria prevalence is very high( 4 ), in 2021 Uganda was ranked third among the twenty nine countries with the highest global burden of malaria cases ( 5 ). Most of the malaria deaths have been reported to occur at home without receiving appropriate medical care and when care is sought of, it’s always too late( 6 ). Early response to diagnosis and appropriate treatment have proved to be the cornerstone of successful malaria control through reduction of illness progression to severe stages which in turn reduce mortality and morbidity rates, and onward transmission( 7 , 8 ). Studies have shown that the risk of death from severe malaria is greatest within the first day of infection( 9 ). However, in most of the endemic countries an extended time lag elapses before start of appropriate anti-malarial treatment is given to patients( 2 ). The World Health Organization established that timely diagnosis and appropriate treatment of malaria should occur within one day of the onset of malaria symptoms( 10 ). However, most of the African countries, Uganda inclusive are very far from meeting such a target( 11 ). Despite the Uganda Malaria Reduction and Elimination Strategic Plan 2021–2025 which aims to reduce malaria infections by 50 percent, morbidity by 50 percent and mortality by 75% by 2025 ( 12 ), malaria prevalence has remained high in Uganda among children under 5 years old( 4 ). Early diagnosis and prompt treatment of malaria remains a global malaria control strategy and depends on correct recognition of malaria signs and symptoms, presentation at a medical establishment with trained staff, treatment based on established criteria and proper adherence to treatment regime( 8 ). Available literature show individual and structural barriers to effective and timely treatment of malaria. These include access to a health care facility, availability of drugs, quality of care received, traditional beliefs, socio economic status, knowledge of malaria transmission and prevention, and perceived severity of disease symptoms( 8 , 13 ). Analyzing such factors taking into account time to treatment, can help identify appropriate and strengthen interventions that aim to improve timely diagnosis and treatment of malaria for high risk subpopulations (children under five years). The main aim of this study was therefore to assess the determinants of time to treatment for children under five years in Uganda using the survival analysis statistical techniques. Methods Data used for the analysis The study used secondary data from the 2016 Uganda Demographic and Health survey (UDHS16). The data collection for the UDHS16 was implemented between 15 June and 18 December 2016 by the Uganda Bureau of Statistics (UBOS) in collaboration with the Ministry of Health (MOH). Sample design UDHS16 sample was stratified (urban/rural) and selected in two stages. In the first stage, 697 Enumeration Areas (EAs) were selected from the 2014 Uganda National Population and Housing Census: 162 EAs in urban areas and 535 in rural areas. Households constituted the second stage of sampling. Using the UDHS16 secondary dataset, a representative sample of 20,880 households (30 per EA) and a total of 18,506 women were successfully interviewed and data on their birth history were collected resulting into a sample of 4,063 under5 children who had had fever (proxy for malaria) two weeks prior to the UDHS16 survey. This sample of 4,063 was used for analysis. Measurements and study variables Time to malaria treatment, the outcome variable of this study was defined as a time taken to onset of malaria treatment after a child indicated signs (fever) of the disease. Mothers were asked the number of days taken before first malaria treatment was commenced. Key variables captured included; socio-demographics of the mother like her; age, education level, occupation, marital status, residence and wealth index. Treatment seeking behavioural factors considered included health treatment decision maker, seeking malaria treatment from a community health worker/Village health teams. Accessibility of health services variables included: distance to nearest health facility and frequency of listening to a radio. Data processing and analysis Cox regression model was applied to identify factors associated with time to malaria treatment. We weighted data to account for the complex design of national demographic health surveys. We tested whether the relative risk of an event was constant over time (the Proportional Hazard Assumption (PHA)) by using Schoenfeld residual tests. Cox regression model was computed for both at bi-variable and multivariate analysis and final results were taken as significance at 5% level. Hazard ratio (HR) with its respective 95% confidence interval (CI) were reported to show the strength of association. Ethical clearance Ethical approval was not necessary for this study as the data were available after permission was granted for this study by the DHS Program ( https://dhsprogram.com/ ). Results Demographic and socio-economic characteristics and time to malaria treatment Table 1 . Association between demographic and socio-economic characteristics and time to malaria treatment Table 1 Association between demographic and socio-economic characteristics and time to malaria treatment Time to malaria treatment Variables Prompt (within 24 hours) (%) Delayed (beyond 24 hours)(%) N P-value Residence of caregiver 0.1920 Urban 62.6 37.4 598 Rural 58.7 41.3 3336 Sex of the household head 0.5073 Male 59.7 40.3 2906 Female 58.3 41.7 1028 Caregiver’s/mother’s Age 0.4126 15–19 55.4 44.6 269 20–24 58.0 42.0 1083 25–29 58.8 41.2 1006 30–34 62.6 37.4 767 35–39 62.0 38.0 506 40–44 56.1 43.9 244 45–49 57.8 42.2 59 Education level of caregiver 0.0060 None 61.5 38.5 470 Primary 58.0 42.1 2542 Secondary 59.3 40.7 771 Post-secondary 75.5 24.5 150 Marital status of caregiver 0.4887 never married 61.3 38.7 165 married/living together 59.7 40.3 3269 widowed/divorced/Separated 56.3 43.8 501 Sex of child 0.8467 Male 59.1 40.9 1998 Female 59.5 40.5 1936 Treatment decision maker 0.0042 Mother 58.7 41.3 1119 Mother and husband 64.7 35.3 1132 Husband only 55.1 44.9 1001 Others 57.6 42.4 682 Occupation 0.0176 Non-agricultural 61.9 38.2 1958 Agricultural 56.8 43.2 1976 Wealth index 0.0123 Poor Middle Rich 58.3 55.3 63.7 41.8 44.7 36.3 2016 747 1171 Frequency of Listening to radio 0.0029 Not at all At most once a week At least once a week 56.4 66.2 58.9 43.6 33.8 41.2 1098 617 2219 Place first visited for malaria treatment 0.6443 Government facility Private facility 58.7 59.4 41.3 40.7 1609 2165 CHWs/VHTs Others 65.3 63.6 34.7 36.4 103 58 Sought treatment from Community Health worker/VHT 0.5007 No Yes 59.2 62.8 40.8 37.2 3827 107 Distance to nearby health facility 0.0109 Very near Far away from homestead 61.8 56.4 38.2 43.6 1800 2134 Region Central Eastern Northern Western 63.7 55.2 65.5 49.8 36.3 44.8 34.6 50.2 859 1480 1111 483 0.0000 Total 59.3 40.7 4063 Table 1 should be placed here Forty one percent of children were found to have delayed (more than 24 hours) to receive their first malaria treatment. Table 1 shows bivariate results of demographic and socio-economic characteristics associated with time to treatment using UDHS16 data. Seventy six percent of children with mothers who had attained post-secondary level of education, were significantly associated with faster time to treatment of malaria. Sixty five percent of children whose mothers jointly decides on health care with their spouse, were significantly associated with faster malaria treatment. Results also show that sixty two percent of children whose mother’s occupation was non-agricultural promptly sought for malaria treatment compared to those in agricultural activities. Sixty four percent of children from mothers who were categorized in the richer wealth quintile, were significantly associated with faster time to malaria treatment compared to those in middle or poor quintiles. Sixty six percent of children whose mothers listened to radio were associated with faster malaria treatment compared to those who never listened to radio. Sixty two percent of children whose mothers were near (less than 5kms) the health facility were associated with faster malaria treatment compared to those who were far from the facility. Fifty percent of the children in Western Uganda had significantly delayed time to treatment of malaria much higher compared to other regions of the country. Factors influencing time to malaria treatment in Uganda Table 2 : Multi-variable Cox regression model for time to malaria treatment among children under five of Uganda. (n = 4,063) Table 2 Multi-variable Cox regression model for time to malaria treatment among children under five of Uganda. (n = 4,063) Variables HR (95% CI) Age of caregiver 15–19 1 1 20–24 0.95 0.85–1.07 25–29 0.97 0.86–1.09 30–34 0.97 0.86–1.09 35–39 0.96 0.84–1.11 40–44 1.02 0.89–1.18 45–49 0.96 0.76–1.21 Wealth index Poor 1 1 Middle 1.06 0.97–1.15 Rich 1.03 0.93–1.14 Health decision maker* Mother only 1 1 Mother & husband 1.11 1.02–1.21 Husband only 0.95 0.86–1.05 Others 1.06 0.96–1.17 Treatment provided by CHW/VHT* No 1 1 Yes 1.17 1.02–1.34 Education level No education 1 1 Primary 0.97 0.88–1.06 Secondary 0.93 0.83–1.05 Post-secondary 1.16 0.97–1.39 Distance to nearby health facility Very near 1 1 Far away from homestead 0.94 0.88–1.01 Region* Central 1 1 Eastern Northern Western 1.01 1.19 0.84 0.90–1.13 1.04–1.36 0.73–0.96 Frequency of Listening to radio* Not at all 1 1 At most once a week 1.23 1.11–1.36 At least once a week 1.11 1.02–1.21 Sex of child Male 1 1 Female 0.98 0.93–1.04 Table 2 should be placed here. Results from the multi-variable Cox regression model (Table 2 ) show that the rate of time to malaria treatment for children whose mothers jointly made health care decision with their spouse, were associated with faster treatment of malaria compared to when mothers made decisions alone (HR = 1.11; 95% CI: 1.02–1.21). Children whose mothers sought malaria treatment from the community health workers were 1.17 faster to treating malaria compared to those who did not (HR = 1.17; 95% CI: 1.02–1.34). Results from Table 2 further indicate that children whose mothers were from Western region, had delayed time to malaria treatment compared to those in Central region (HR = 0.84; 95% CI: 0.73–0.96). Children whose mothers listened to radio at least once a week were 1.10faster to treating malaria compared to those who did not listen to radio at all (HR = 1.11;95% CI: 1.02–1.21). Discussion Forty one percent of the children who had delayed for treatment of malaria (took more than 24 hours). This study found out that faster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region of Uganda and increased frequency of listening to radio. A similar study carried out in Equatorial Guinea ( 6 ) and in Myanmar ( 14 ) collaborate our findings on decision making. The Myanmar study show that family decision was a significant factor to faster time to treatment of malaria. In Myanmar, families whose mothers could make decisions or co-decisions with the spouse, were more likely to seek treatment in time. A study on impact of modernization and development in Uganda, indicated that women contribute positively to family health care ( 15 ). Caregivers/mothers who frequently listen to radios were significantly associated with prompt malaria treatment, pass on information. The findings are similar to those of a study carried out in Eritrea which indicated that caregiver’s exposure to information about malaria significantly influenced their ability to be knowledgeable on the frequent signs and symptoms of malaria( 16 ). Caregivers that sought malaria treatment from community health workers/ village health teams significantly received earlier malaria treatment. The findings are similar to a study in Sub-Saharan Africa about the medicine sellers and malaria treatment which reported that management of illness by community health workers improves timely access to treatment and is associated with a reduction in malaria infections( 17 ). Similarly a study in Myanmar found out that a large proportion of febrile patients sought early advice or treatment from community health workers and a high proportion of the febrile was diagnosed by clinical symptoms for malaria and most of the microscopy or RDT were given by outreach service of Non-Governmental Organizations and community health workers( 14 ). Children whose mothers were from Western region had delayed time to malaria treatment compared to other regions of the country. The results are consistent with findings of a study in Sub Saharan Africa on timeliness of malaria treatment in children under five years of Age which showed a significant association between region and time to malaria treatment( 18 ). Studies show that in Western region of Uganda, mothers move longer distances to access health care services( 4 ) a cause to delayed time to treatment of malaria. Government of Uganda has also been implementing the Integrated Community Case Management (ICCM) where community health workers are provided with testing kits for malaria and they also do treat the diseases. The ICCM programme covers more of the high malaria endemic regions especially the north and the eastern regions of the country with more districts in Western region not covered under this programme( 19 ). The Government of Uganda has been undertaking the distribution of treated mosquito nets, indoor residual spraying. 60% of children under 5 & 65% of pregnant women sleep under treated mosquito net. Pregnant women received 3 + doses of SP/Fansidar to prevent malaria in pregnancy( 19 ).This study has some limitations. Firstly, the treatment seeking behaviour registered was based on reported fever (no assurance whether it was truly diagnosed as malaria) thus some cases may not have been malaria. However, this would not have changed the behaviour of caregivers because they thought it was malaria and proceeded accordingly. The study used UDHS16 and at the time of analyses, a number of changes could have occurred. Conclusions Faster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region and increased frequency of listening to radio. Thus malaria control initiatives should focus its strategy on strengthening health interventions through introduction of programmes that can empower joint spousal decision making capabilities, facilitations and equipping of community health workers with malaria treatment, and frequent use of radios to relay malaria messages to communities Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials Data for this study were sourced from Demographic and Health surveys (DHS) Here: http://dhsprogram.com/data/available-datasets.cfm. Competing interests The authors declare that they have no competing interests. Funding The authors have no support or funding to report Authors’ contributions JBA and EK contributed to the conception and design of the study. They both did the acquisition of data, conducted the statistical analysis and interpreted the original results. Both authors wrote or reviewed and approved the final manuscript. Acknowledgements The authors thank the MEASURE DHS for their support and for free access to the data used in this study. References Sonkong K, Chaiklieng S, Neave P, Suggaravetsiri P (2015) Factors affecting delay in seeking treatment among malaria patients along Thailand-Myanmar border in Tak Province, Thailand. Malar J 14(1):1–8 World Health Organization. Global Malaria Programme. Eliminating malaria. Geneva: World Health Organization [Internet]. World Health Organization (2015) http://www.who.int/malaria/publications/world-malaria-report-2015/report/en/ Global fund. The Global Fund Results Report 2022 [Internet] (2022) https://www.theglobalfund.org/media/12265/corporate_2022resultsreport_report_en.pdf Roberts D, Matthews G (2016) Risk factors of malaria in children under the age of five years old in Uganda. Malar J 15(1):1–12 World Health Organization (2022) World malaria report 2022. Geneva Romay-Barja M, Cano J, Ncogo P, Nseng G, Santana-Morales MA, Valladares B et al (2016) Determinants of delay in malaria care-seeking behaviour for children 15 years and under in Bata district, Equatorial Guinea. Malar J 15(1):1–8 Dillip A, Hetzel MW, Gosoniu D, Kessy F, Lengeler C, Mayumana I et al (2009) Socio-cultural factors explaining timely and appropriate use of health facilities for degedege in south-eastern Tanzania. Malar J 8(1):1–12 Lindblade KA, O’Neill DB, Mathanga DP, Katungu J, Wilson ML (2000) Treatment for clinical malaria is sought promptly during an epidemic in a highland region of Uganda. Trop Med Int Heal 5(12):865–875 World Health Organization (2014) Severe Malaria. Trop Med Int Heal 19(suppl 1):7–131 WHO. The African Summit on Roll Back Malaria, Abuja, Nigeria. World Health Organization. [Internet]. Geneva (2000) https://apps.who.int/iris/handle/10665/67815 Shah JA, Emina JBO, Eckert E, Ye Y (2015) Prompt access to effective malaria treatment among children under five in sub-Saharan Africa: A multi-country analysis of national household survey data. Malar J 14(1):1–14 MOH. U.S, PRESIDENT’S MALARIA (2020) INITIATIVE UGANDA Malaria Operational Plan FY 2021. p. 26 Baird JK (2005) Effectiveness of Antimalarial Drugs. N Engl J Med 352(15):1565–1577 Xu JW, Xu QZ, Liu H, Zeng YR (2012) Malaria treatment-seeking behaviour and related factors of Wa ethnic minority in Myanmar: A cross-sectional study. Malar J [Internet]. ;11(1):1. Available from: Malaria Journal Singh DAK, Earnest J, Lample M (2015) Modernization and Development: Impact on Health Care Decision-Making in Uganda. Health Care Women Int 36(6):637–654 Andegiorgish AK (2019) Knowledge, Attitude and Treatment Seeking Behavior for Malaria in May-Aynee Administration, Eritrea. Biomed J Sci Tech Res 22(1):16393–16399 Goodman C, Brieger W, Unwin A, Mills A, Meek S, Greer G (2007) Medicine sellers and malaria treatment in sub-Saharan Africa: What do they do and how can their practice be improved? Am J Trop Med Hyg 77(SUPPL 6):203–218 Emina JBO, Ye Y (2014) Timeliness of Malaria Treatment in Children Under Five Years of Age in Sub Saharan Africa: A Multicountry Analysis of National Household Survey Data. Who. Maryland, USA:MEASURE Evaluation MoH (2016) Annual Health Sector Performance Report 2020/21. Kampala Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-4726273","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":325828844,"identity":"83cd562f-c744-4b18-b1b6-57d40b578aa8","order_by":0,"name":"John Bosco Asiimwe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYFACxoYDYGoGM4iWkCFFC1sCSAsPCbZJ8BiAKMJa+PsPNx662WYjzzy75/OrGzUWPAzsh49uwGv2jcSGw7ltaYaNc85us845BnQYT1raDbzW3GAEatl2mLFxRu424xw2oBYJHjO8WuTPHwRp+W/fOCPnmXHOPyK0GBwAOWzbgUSgFubHuW1EaDEE++VfcnLjnGNmzLl9EjxshPwid/744885Z+xsN85uBjK+1cnxsx8+ht/7cOsaGNgkQAw2opSDgDwDA/MHolWPglEwCkbBiAIAYQBQVYHBR44AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-9505-4957","institution":"Makerere University","correspondingAuthor":true,"prefix":"","firstName":"John","middleName":"Bosco","lastName":"Asiimwe","suffix":""},{"id":325828845,"identity":"2a221129-eb85-4887-82e4-0ab619ce63e4","order_by":1,"name":"Eriot Kadubira","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Eriot","middleName":"","lastName":"Kadubira","suffix":""}],"badges":[],"createdAt":"2024-07-11 19:02:51","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-4726273/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4726273/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60289259,"identity":"c3122dea-6dd0-42f2-ac09-0eb2041b0cca","added_by":"auto","created_at":"2024-07-15 08:33:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":741170,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4726273/v1/0473c9e7-1ff1-4b81-b4a3-0235c260ad80.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eTimeliness of Malaria Treatment in Children Under Five Years in Uganda: \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAn Analysis of 2016 Demographic Health Survey Data\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMalaria is ranked among the diseases that have contributed greatly to the death of many children and adults worldwide(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Globally about 438,000 deaths caused by malaria were recorded in 2015, 90% of these deaths occurred in Sub Saharan Africa and almost 71% of the deaths were for children under five years (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Malaria accounts for about 10% of all death among under 5 children in Sub Saharan Africa.\u003c/p\u003e \u003cp\u003eUganda has made great strides in curbing malaria prevalence from 42% in 2009 to 9% in 2018(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Despite all the interventions to reduce malaria transmissions like the distribution of free insecticide-treated nets and indoor residual spraying in a limited number of districts where malaria prevalence is very high(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), in 2021 Uganda was ranked third among the twenty nine countries with the highest global burden of malaria cases (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost of the malaria deaths have been reported to occur at home without receiving appropriate medical care and when care is sought of, it\u0026rsquo;s always too late(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Early response to diagnosis and appropriate treatment have proved to be the cornerstone of successful malaria control through reduction of illness progression to severe stages which in turn reduce mortality and morbidity rates, and onward transmission(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies have shown that the risk of death from severe malaria is greatest within the first day of infection(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). However, in most of the endemic countries an extended time lag elapses before start of appropriate anti-malarial treatment is given to patients(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The World Health Organization established that timely diagnosis and appropriate treatment of malaria should occur within one day of the onset of malaria symptoms(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, most of the African countries, Uganda inclusive are very far from meeting such a target(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite the Uganda Malaria Reduction and Elimination Strategic Plan 2021\u0026ndash;2025 which aims to reduce malaria infections by 50 percent, morbidity by 50 percent and mortality by 75% by 2025 (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), malaria prevalence has remained high in Uganda among children under 5 years old(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Early diagnosis and prompt treatment of malaria remains a global malaria control strategy and depends on correct recognition of malaria signs and symptoms, presentation at a medical establishment with trained staff, treatment based on established criteria and proper adherence to treatment regime(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAvailable literature show individual and structural barriers to effective and timely treatment of malaria. These include access to a health care facility, availability of drugs, quality of care received, traditional beliefs, socio economic status, knowledge of malaria transmission and prevention, and perceived severity of disease symptoms(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Analyzing such factors taking into account time to treatment, can help identify appropriate and strengthen interventions that aim to improve timely diagnosis and treatment of malaria for high risk subpopulations (children under five years). The main aim of this study was therefore to assess the determinants of time to treatment for children under five years in Uganda using the survival analysis statistical techniques.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData used for the analysis\u003c/h2\u003e \u003cp\u003eThe study used secondary data from the 2016 Uganda Demographic and Health survey (UDHS16). The data collection for the UDHS16 was implemented between 15 June and 18 December 2016 by the Uganda Bureau of Statistics (UBOS) in collaboration with the Ministry of Health (MOH).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSample design\u003c/h2\u003e \u003cp\u003eUDHS16 sample was stratified (urban/rural) and selected in two stages. In the first stage, 697 Enumeration Areas (EAs) were selected from the 2014 Uganda National Population and Housing Census: 162 EAs in urban areas and 535 in rural areas. Households constituted the second stage of sampling. Using the UDHS16 secondary dataset, a representative sample of 20,880 households (30 per EA) and a total of 18,506 women were successfully interviewed and data on their birth history were collected resulting into a sample of 4,063 under5 children who had had fever (proxy for malaria) two weeks prior to the UDHS16 survey. This sample of 4,063 was used for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMeasurements and study variables\u003c/h2\u003e \u003cp\u003eTime to malaria treatment, the outcome variable of this study was defined as a time taken to onset of malaria treatment after a child indicated signs (fever) of the disease. Mothers were asked the number of days taken before first malaria treatment was commenced. Key variables captured included; socio-demographics of the mother like her; age, education level, occupation, marital status, residence and wealth index. Treatment seeking behavioural factors considered included health treatment decision maker, seeking malaria treatment from a community health worker/Village health teams. Accessibility of health services variables included: distance to nearest health facility and frequency of listening to a radio.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData processing and analysis\u003c/h2\u003e \u003cp\u003eCox regression model was applied to identify factors associated with time to malaria treatment. We weighted data to account for the complex design of national demographic health surveys. We tested whether the relative risk of an event was constant over time (the Proportional Hazard Assumption (PHA)) by using Schoenfeld residual tests. Cox regression model was computed for both at bi-variable and multivariate analysis and final results were taken as significance at 5% level. Hazard ratio (HR) with its respective 95% confidence interval (CI) were reported to show the strength of association.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEthical clearance\u003c/h2\u003e \u003cp\u003eEthical approval was not necessary for this study as the data were available after permission was granted for this study by the DHS Program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dhsprogram.com/\u003c/span\u003e\u003cspan address=\"https://dhsprogram.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDemographic and socio-economic characteristics and time to malaria treatment\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eAssociation between demographic and socio-economic characteristics and time to malaria treatment\u003c/b\u003e\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\u003e\u003cb\u003eAssociation between demographic and socio-economic characteristics and time to malaria treatment\u003c/b\u003e\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTime to malaria treatment\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePrompt\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(within 24 hours) (%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eDelayed\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(beyond 24 hours)(%)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eN\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence of caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.1920\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of the household head\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.5073\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiver\u0026rsquo;s/mother\u0026rsquo;s Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.4126\u003c/b\u003e\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\u003e55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e58.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e62.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e62.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e56.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\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\u003e57.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level of caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0060\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status of caregiver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.4887\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emarried/living together\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ewidowed/divorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.8467\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment decision maker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother and husband\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHusband only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e682\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0176\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-agricultural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgricultural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1976\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0123\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003cp\u003e55.3\u003c/p\u003e \u003cp\u003e63.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003cp\u003e44.7\u003c/p\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003cp\u003e747\u003c/p\u003e \u003cp\u003e1171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of Listening to radio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003cp\u003eAt most once a week\u003c/p\u003e \u003cp\u003eAt least once a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003cp\u003e66.2\u003c/p\u003e \u003cp\u003e58.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.6\u003c/p\u003e \u003cp\u003e33.8\u003c/p\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1098\u003c/p\u003e \u003cp\u003e617\u003c/p\u003e \u003cp\u003e2219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace first visited for malaria treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.6443\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGovernment facility\u003c/p\u003e \u003cp\u003ePrivate facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.7\u003c/p\u003e \u003cp\u003e59.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1609\u003c/p\u003e \u003cp\u003e2165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHWs/VHTs\u003c/p\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65.3\u003c/p\u003e \u003cp\u003e63.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e103\u003c/p\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSought treatment from Community Health worker/VHT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.5007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003cp\u003e62.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.8\u003c/p\u003e \u003cp\u003e37.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3827\u003c/p\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistance to nearby health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0109\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery near\u003c/p\u003e \u003cp\u003eFar away from homestead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.8\u003c/p\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003cp\u003e43.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1800\u003c/p\u003e \u003cp\u003e2134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003cp\u003eCentral\u003c/p\u003e \u003cp\u003eEastern\u003c/p\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63.7\u003c/p\u003e \u003cp\u003e55.2\u003c/p\u003e \u003cp\u003e65.5\u003c/p\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003cp\u003e44.8\u003c/p\u003e \u003cp\u003e34.6\u003c/p\u003e \u003cp\u003e50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e859\u003c/p\u003e \u003cp\u003e1480\u003c/p\u003e \u003cp\u003e1111\u003c/p\u003e \u003cp\u003e483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.0000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eshould be placed here\u003c/b\u003e\u003c/p\u003e \u003cp\u003eForty one percent of children were found to have delayed (more than 24 hours) to receive their first malaria treatment. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows bivariate results of demographic and socio-economic characteristics associated with time to treatment using UDHS16 data. Seventy six percent of children with mothers who had attained post-secondary level of education, were significantly associated with faster time to treatment of malaria. Sixty five percent of children whose mothers jointly decides on health care with their spouse, were significantly associated with faster malaria treatment. Results also show that sixty two percent of children whose mother\u0026rsquo;s occupation was non-agricultural promptly sought for malaria treatment compared to those in agricultural activities. Sixty four percent of children from mothers who were categorized in the richer wealth quintile, were significantly associated with faster time to malaria treatment compared to those in middle or poor quintiles. Sixty six percent of children whose mothers listened to radio were associated with faster malaria treatment compared to those who never listened to radio. Sixty two percent of children whose mothers were near (less than 5kms) the health facility were associated with faster malaria treatment compared to those who were far from the facility. Fifty percent of the children in Western Uganda had significantly delayed time to treatment of malaria much higher compared to other regions of the country.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFactors influencing time to malaria treatment in Uganda\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: \u003cb\u003eMulti-variable Cox regression model for time to malaria treatment among children under five of Uganda. (n\u0026thinsp;=\u0026thinsp;4,063)\u003c/b\u003e\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\u003eMulti-variable Cox regression model for time to malaria treatment among children under five of Uganda. (n\u0026thinsp;=\u0026thinsp;4,063)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of caregiver\u003c/p\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u0026ndash;1.07\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026ndash;1.09\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026ndash;1.09\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u0026ndash;1.11\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.89\u0026ndash;1.18\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=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;1.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026ndash;1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth decision maker*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother \u0026amp; husband\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHusband only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026ndash;1.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment provided by CHW/VHT*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u0026ndash;1.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u0026ndash;1.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-secondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;1.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistance to nearby health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery near\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFar away from homestead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u0026ndash;1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion*\u003c/p\u003e \u003cp\u003e\u003cem\u003eCentral\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003cp\u003e1.19\u003c/p\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u0026ndash;1.13\u003c/p\u003e \u003cp\u003e1.04\u0026ndash;1.36\u003c/p\u003e \u003cp\u003e0.73\u0026ndash;0.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of Listening to radio*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt most once a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.11\u0026ndash;1.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAt least once a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.02\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex of child\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026ndash;1.04\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e should be placed here.\u003c/p\u003e \u003cp\u003eResults from the multi-variable Cox regression model (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) show that the rate of time to malaria treatment for children whose mothers jointly made health care decision with their spouse, were associated with faster treatment of malaria compared to when mothers made decisions alone (HR\u0026thinsp;=\u0026thinsp;1.11; 95% CI: 1.02\u0026ndash;1.21). Children whose mothers sought malaria treatment from the community health workers were 1.17 faster to treating malaria compared to those who did not (HR\u0026thinsp;=\u0026thinsp;1.17; 95% CI: 1.02\u0026ndash;1.34). Results from Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e further indicate that children whose mothers were from Western region, had delayed time to malaria treatment compared to those in Central region (HR\u0026thinsp;=\u0026thinsp;0.84; 95% CI: 0.73\u0026ndash;0.96). Children whose mothers listened to radio at least once a week were 1.10faster to treating malaria compared to those who did not listen to radio at all (HR\u0026thinsp;=\u0026thinsp;1.11;95% CI: 1.02\u0026ndash;1.21).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eForty one percent of the children who had delayed for treatment of malaria (took more than 24 hours). This study found out that faster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region of Uganda and increased frequency of listening to radio. A similar study carried out in Equatorial Guinea (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) and in Myanmar (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) collaborate our findings on decision making. The Myanmar study show that family decision was a significant factor to faster time to treatment of malaria. In Myanmar, families whose mothers could make decisions or co-decisions with the spouse, were more likely to seek treatment in time. A study on impact of modernization and development in Uganda, indicated that women contribute positively to family health care (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCaregivers/mothers who frequently listen to radios were significantly associated with prompt malaria treatment, pass on information. The findings are similar to those of a study carried out in Eritrea which indicated that caregiver\u0026rsquo;s exposure to information about malaria significantly influenced their ability to be knowledgeable on the frequent signs and symptoms of malaria(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCaregivers that sought malaria treatment from community health workers/ village health teams significantly received earlier malaria treatment. The findings are similar to a study in Sub-Saharan Africa about the medicine sellers and malaria treatment which reported that management of illness by community health workers improves timely access to treatment and is associated with a reduction in malaria infections(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Similarly a study in Myanmar found out that a large proportion of febrile patients sought early advice or treatment from community health workers and a high proportion of the febrile was diagnosed by clinical symptoms for malaria and most of the microscopy or RDT were given by outreach service of Non-Governmental Organizations and community health workers(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChildren whose mothers were from Western region had delayed time to malaria treatment compared to other regions of the country. The results are consistent with findings of a study in Sub Saharan Africa on timeliness of malaria treatment in children under five years of Age which showed a significant association between region and time to malaria treatment(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Studies show that in Western region of Uganda, mothers move longer distances to access health care services(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) a cause to delayed time to treatment of malaria. Government of Uganda has also been implementing the Integrated Community Case Management (ICCM) where community health workers are provided with testing kits for malaria and they also do treat the diseases. The ICCM programme covers more of the high malaria endemic regions especially the north and the eastern regions of the country with more districts in Western region not covered under this programme(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The Government of Uganda has been undertaking the distribution of treated mosquito nets, indoor residual spraying. 60% of children under 5 \u0026amp; 65% of pregnant women sleep under treated mosquito net. Pregnant women received 3\u0026thinsp;+\u0026thinsp;doses of SP/Fansidar to prevent malaria in pregnancy(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).This study has some limitations. Firstly, the treatment seeking behaviour registered was based on reported fever (no assurance whether it was truly diagnosed as malaria) thus some cases may not have been malaria. However, this would not have changed the behaviour of caregivers because they thought it was malaria and proceeded accordingly. The study used UDHS16 and at the time of analyses, a number of changes could have occurred.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFaster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region and increased frequency of listening to radio.\u003c/p\u003e \u003cp\u003eThus malaria control initiatives should focus its strategy on strengthening health interventions through introduction of programmes that can empower joint spousal decision making capabilities, facilitations and equipping of community health workers with malaria treatment, and frequent use of radios to relay malaria messages to communities\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for this study were sourced from Demographic and Health surveys (DHS)\u003c/p\u003e\n\u003cp\u003eHere: http://dhsprogram.com/data/available-datasets.cfm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no support or funding to report\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJBA and EK contributed to the conception and design of the study. They both did the acquisition of data, conducted the statistical analysis and interpreted the original results. Both authors wrote or reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the MEASURE DHS for their support and for free access to the data used in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSonkong K, Chaiklieng S, Neave P, Suggaravetsiri P (2015) Factors affecting delay in seeking treatment among malaria patients along Thailand-Myanmar border in Tak Province, Thailand. Malar J 14(1):1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global Malaria Programme. Eliminating malaria. Geneva: World Health Organization [Internet]. World Health Organization (2015) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.who.int/malaria/publications/world-malaria-report-2015/report/en/\u003c/span\u003e\u003cspan address=\"http://www.who.int/malaria/publications/world-malaria-report-2015/report/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal fund. The Global Fund Results Report 2022 [Internet] (2022) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.theglobalfund.org/media/12265/corporate_2022resultsreport_report_en.pdf\u003c/span\u003e\u003cspan address=\"https://www.theglobalfund.org/media/12265/corporate_2022resultsreport_report_en.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoberts D, Matthews G (2016) Risk factors of malaria in children under the age of five years old in Uganda. Malar J 15(1):1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2022) World malaria report 2022. Geneva\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomay-Barja M, Cano J, Ncogo P, Nseng G, Santana-Morales MA, Valladares B et al (2016) Determinants of delay in malaria care-seeking behaviour for children 15 years and under in Bata district, Equatorial Guinea. Malar J 15(1):1\u0026ndash;8\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDillip A, Hetzel MW, Gosoniu D, Kessy F, Lengeler C, Mayumana I et al (2009) Socio-cultural factors explaining timely and appropriate use of health facilities for degedege in south-eastern Tanzania. Malar J 8(1):1\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindblade KA, O\u0026rsquo;Neill DB, Mathanga DP, Katungu J, Wilson ML (2000) Treatment for clinical malaria is sought promptly during an epidemic in a highland region of Uganda. Trop Med Int Heal 5(12):865\u0026ndash;875\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization (2014) Severe Malaria. Trop Med Int Heal 19(suppl 1):7\u0026ndash;131\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. The African Summit on Roll Back Malaria, Abuja, Nigeria. World Health Organization. [Internet]. Geneva (2000) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://apps.who.int/iris/handle/10665/67815\u003c/span\u003e\u003cspan address=\"https://apps.who.int/iris/handle/10665/67815\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah JA, Emina JBO, Eckert E, Ye Y (2015) Prompt access to effective malaria treatment among children under five in sub-Saharan Africa: A multi-country analysis of national household survey data. Malar J 14(1):1\u0026ndash;14\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMOH. U.S, PRESIDENT\u0026rsquo;S MALARIA (2020) INITIATIVE UGANDA Malaria Operational Plan FY 2021. p. 26\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaird JK (2005) Effectiveness of Antimalarial Drugs. N Engl J Med 352(15):1565\u0026ndash;1577\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu JW, Xu QZ, Liu H, Zeng YR (2012) Malaria treatment-seeking behaviour and related factors of Wa ethnic minority in Myanmar: A cross-sectional study. Malar J [Internet]. ;11(1):1. Available from: Malaria Journal\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh DAK, Earnest J, Lample M (2015) Modernization and Development: Impact on Health Care Decision-Making in Uganda. Health Care Women Int 36(6):637\u0026ndash;654\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndegiorgish AK (2019) Knowledge, Attitude and Treatment Seeking Behavior for Malaria in May-Aynee Administration, Eritrea. Biomed J Sci Tech Res 22(1):16393\u0026ndash;16399\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodman C, Brieger W, Unwin A, Mills A, Meek S, Greer G (2007) Medicine sellers and malaria treatment in sub-Saharan Africa: What do they do and how can their practice be improved? Am J Trop Med Hyg 77(SUPPL 6):203\u0026ndash;218\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmina JBO, Ye Y (2014) Timeliness of Malaria Treatment in Children Under Five Years of Age in Sub Saharan Africa: A Multicountry Analysis of National Household Survey Data. Who. Maryland, USA:MEASURE Evaluation\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoH (2016) Annual Health Sector Performance Report 2020/21. Kampala\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Makerere University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Malaria, treatment, Uganda, time, mothers","lastPublishedDoi":"10.21203/rs.3.rs-4726273/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4726273/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMalaria is ranked among the major causes of morbidity and mortality in children under 5 years of age in Uganda. Prompt and early appropriate malaria treatment can prevent progression of illness to severe stages, thereby mitigating mortality and morbidity. Therefore, this study aimed at determining the factors associated with timeliness to malaria treatment in children under five years in Uganda.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod: \u003c/strong\u003eThis study used 2016 Uganda Demographic and Health Survey data and a total of 4,063 children under age of five years who had fever as a proxy for malaria two weeks prior to the survey were included. The median time to malaria treatment using Kaplan Meier curve were computed. A multivariable Cox regression model were fitted to establish factors associated with time to malaria treatment. Proportional hazard assumption was checked graphically and using Schoenfeld residual statistical test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eForty one percent of the children delayed to receive prompt malaria treatment beyond the recommended 24 hours. The median time to malaria treatment was 24 hours after onset of malaria symptoms. Children whose mothers made decisions jointly as a wife and a spouse on treatment were associated with faster time to malaria treatment (HR=1.11, 95%CI: 1.02-1.21) compared to when the mother made decisions alone. Children whose mothers sought treatment from community health workers were associated with faster time to malaria treatment (HR=1.17, 95%CI: 1.02-1.34) compared to those who did not. Children whose mothers/caregivers were from Western region (HR=0.84, 95%CI: 0.73-0.96) of the country were associated with delayed time to malaria treatment compared to other regions of the country. Similarly, children whose mothers frequently listened to radio were significantly associated with faster time (HR=1.11, 95%CI: 1.02-1.21) to treatment of malaria compared to those who did not listen to radio.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eFaster time to malaria treatment was significantly associated with joint spousal health decision making, utilization of community health workers, not being in Western region of Uganda and frequency of listening to radio. Thus malaria control initiatives should focus its strategy on strengthening health interventions through introduction of programmes that can empower joint spousal decision making capabilities, facilitations and equipping of community health workers with malaria treatment, and increased frequent use of radios to relay malaria messages to communities.\u003c/p\u003e","manuscriptTitle":"Timeliness of Malaria Treatment in Children Under Five Years in Uganda: An Analysis of 2016 Demographic Health Survey Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 08:25:25","doi":"10.21203/rs.3.rs-4726273/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fcd97a01-6709-4683-b8d4-10511cac3b79","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34475179,"name":"Health Policy"}],"tags":[],"updatedAt":"2024-07-15T08:25:25+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-15 08:25:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4726273","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4726273","identity":"rs-4726273","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}