Factors Associated with Prevalence of Malaria Infection among Children under 5 Years of Age in Mozambique: 2015 vs 2018

Factors Associated with Prevalence of Malaria Infection among Children under 5 Years of Age in Mozambique: 2015 vs 2018 | 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 Factors Associated with Prevalence of Malaria Infection among Children under 5 Years of Age in Mozambique: 2015 vs 2018 Crizolgo De Jesus Salvador, Paulo Arnaldo, Bernardete Xavier Rafael, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-168223/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 still a leading cause of morbidity and mortality among children under five years old in Mozambique. In this study we sought to determine the prevalence of malaria infection and its predictors among children six to 59 months old in Mozambique. Methods: Data from two national malaria indicators surveys in 2015 and 2018 were compared. In both surveys, blood samples were collected among children six to 59 months old to detect Plasmodium falciparum antigen by a rapid diagnostic test, and questionnaires were applied to collect socio-economic, demographic and vector control data from their households. Association of malaria rapid diagnostic test positivity with age, gender, residence, region, use of a vector control intervention, mother’s level of education and wealth index was assessed by logistic regression, using both univariate and multivariate analysis. A complex sampling logistic regression model was used to identify factors associated with malaria infection with estimated adjusted odds ratio and respective 95% confidence intervals. Results: A total of 9,068 children were tested for malaria infection of which 4,640 were in 2015 and 4,428 in 2018. The prevalence of malaria infection was 40.2% and 38.9% in 2015 and 2018, respectively. From 2015 to 2018, insecticide-treated nets ownership increased from 72.3% to 90.2% (p<0.001) and insecticide-treated nets use increased from 45.5% to 72.4% in children under the age of 5 years (p<0.001). In multivariate analysis, malaria infection was associated with region (north and central regions) and rural area for both surveys. Living in households with a wealth quintile lower than the wealthiest was associated with an increased odds of malaria infection (p<0.001). Maternal level of education and absence of an insecticide-treated net in the household were associated with malaria infection in 2015 (p<0.001) but not in 2018. Malaria infection was associated with age older than 12 months in 2015 and with age 24-35 months and 48-59 months in2018. Conclusions: Although insecticide-treated nets ownership and use have increased between the two surveys, prevalence of malaria infection remained stagnant. The main predictors of malaria infection were region, place of residence and socioeconomic status, underscoring the importance of broader developmental and socioeconomic factors on malaria prevalence. Infectious Diseases Malaria P. falciparum children six to 59 months old insecticide treated nets Mozambique Figures Figure 1 Background Malaria is still a leading cause of morbidity and mortality among children under five years of age around the world. In 2018, 228 million cases and 405,000 deaths from malaria were reported globally. The sub-Saharan Africa region accounted for 93% of the cases and 94% of the deaths. Mozambique contributed4% of the global malaria case burden ( 1 ). The distribution of malaria prevalence in Mozambique is heterogeneous, with a higher prevalence in the northern and central regions compared to the southern region ( 2 ). The National Malaria Control Program (NMCP) of Mozambique developed the 2017–2022 National Strategic Plan to implement and monitor interventions for malaria control. In order to reduce the burden of malaria in the country, the NMCP is investing resources in a combination of vector control and case management interventions ( 3 ). However, the impact of the interventions on high risk populations and areas of high prevalence is not yet known. Understanding the factors associated with the prevalence of malaria infection and its distribution is important to improve the planning of national and sub-national malaria control strategies. Previous global research on the factors associated with malaria prevalence and distribution have shown varied results. Some studies have shown that access and use of prevention strategies such as insecticide treated nets (ITNs) and indoor residual spray (IRS) reduced malaria prevalence ( 4 , 5 ) while in others the use of these strategies have shown no significant impact( 6 ). Higher socioeconomic and educational status have also been indicated as protective by some authors ( 7 ) while others found no relation ( 8 ). In this analysis we sought to determine the prevalence of malaria infections and its predictors among children six to fifty-nine months old in Mozambique by comparing the 2015 Malaria, HIV/AIDS, and Immunization Indicator Survey (IMASIDA) and the 2018 Malaria Indicator Survey (MIS). The analysis will provide information on the coverage of interventions for malaria control and factors associated to the prevalence of malaria. These information can support the NMCP to strengthen the planning malaria control interventions. Methods Study setting The analysis is based on two nation-wide surveys. Mozambique is divided in three regions, northern, central, and southern. The northern region includes the provinces of Niassa, Cabo Delgado and Nampula, and the central region includes the provinces of Tete, Zambézia, Manica and Sofala, and the southern region includes the provinces of Inhambane, Gaza, Maputo and Maputo City. Typically, Mozambique has a tropical climate with two distinct seasons: a hot and humid season from October to March and a dry and cool season from April to September, although there are variations depending on the region and altitude. Malaria transmission is higher in the hot and humid season due to the abundance of water and vegetation, which favours breeding of Anopheles mosquitoes. P. falciparum accounts for 90% of all malaria infections ( 9 ). Study Design and data source We conducted a retrospective analysis of data from two community-based surveys conducted in 2015 and 2018. The IMASIDA was conducted from June to September in 2015, while the MIS was conducted from March to June 2018. For both surveys, the sampling was representative nationally, for rural and urban areas, and at the provincial level. Households were selected using data from the General Population and Housing Census 2007 (RGPH 2007). In the first stage of sampling, Enumeration Areas (EAs) were selected from the total EA outlined in the RGPH 2007, with probability-proportional-to-size, in which some were located in urban areas and others in rural areas. A total of 307 EAs, in which 134 (43.6%) were urban, were selected for the IMASIDA 2015 and 224 EAs, in which 92 (41.1%) were urban, were selected for the MIS 2018. In the second sampling stage, all households within the EA were listed followed by random selection of households. A total of 24 and 28 households per EA were selected for the IMASIDA 2015 and for the MIS 2018, respectively. In total, 7,368 households were selected in IMASIDA 2015 and 6,279 households were selected in MIS 2018. Women aged 15–49 years and children aged 6–59 months, who were habitually resident or had spent the night before the survey in the household were eligible for interview and malaria testing respectively. For the IMASIDA, responses rates were 97.6% for selected households and 94.5% for eligible women; for the MIS 2018, response rates were 99.0% for households and 98.3% for eligible women. Data collection For both surveys data was collected from three sources: i) a household questionnaire was used to collect information to determine the household wealth index, information of the household owner-ship and use of insecticide treated nets (ITN), and exposure to indoor residual spraying (IRS); ii) a questionnaire addressed to women aged 15–49 was used to collect information on age, residence history, educational level, intermittent preventive treatment of malaria during pregnancy, use of ITN, treatment of malaria in children under 5 years of age and knowledge of malaria; iii) a biomarkers questionnaire was used to record the results of the malaria and anaemia tests in children 6–59 months of age. Malaria testing Malaria tests were performed using capillary blood samples taken from the fingers or heels of included children. In the IMASIDA 2015, malaria testing was performed using rapid diagnosis test (RDT) SD Bioline Malaria Ag Pf and Pv (Abbott) to detect P. falciparum and P.vivax antigens while in the MIS 2018 the RDT was SD Bioline Malaria Ag Pf (Abbott) which detects only the P. falciparum antigen. Statistical analysis To prepare the data for analysis, the individual members (PR) datasets from both surveys were merged into one dataset. Special (svy) survey commands were used to account for complex multilevel survey design. Data were weighted to account for the differential selection probabilities at the EA, household and individual levels. Only weighted survey data are presented in this manuscript. Socio-economic, demographic and vector control characteristics were compared between 2015 and 2018 using t-student test. Logistic regression was used to evaluate factors associated with presence of Plasmodium sp antigen as detected by RDT among children under 5 years of age (dependent variable). The independent variables included: age; gender; residence (urban vs rural); region (southern, central or northern); use of ITNs; IRS in the past 6 months; highest education level attained by the mother; and wealth index. Multivariate complex sampling logistic regression was used to identify factors associated with malaria infection, with estimated adjusted odds ratio (AOR) and respective 95% confidence intervals (CI). All statistical analyses were performed using Stata, version 15 (Stata Corporation, College Station, Texas). Ethical considerations For both surveys, ethical approval was obtained from the Mozambique National Bioethics Committee for Health (CNBS) prior to data collection, IMASIDA 2015 (42/CNBS/2014) and MIS 2018 (69/CNBS/18). Written informed consent was obtained from study participants. Parental consent was also provided for all children who were tested for malaria and anaemia. Results General characteristics of study participants and prevalence of malaria infection A total of 9,068 children under the age of five years were tested for malaria infection, of which 4,640 (51.2%) from the 2015 survey and 4,428 (48.8%) from the 2018 survey. Table 1 shows the socio-demographic characteristics of study participants for both surveys; no significant differences were found. The proportion of households who owned at least one ITN was significantly higher in 2018, with 72.3% in 2015 and 90.2% in 2018 (p < 0.001). Similarly, the proportion of children under 5 years who reported sleeping under ITN the night before the survey increased from45.5% in 2015 to 72.4% in 2018 (p < 0.001). Table 1 Demographic characteristics of children 6–59 months old and vector control interventions indicators in two surveys in Mozambique, 2015 and 2018. Variable IMASIDA 2015 N = 4640 MIS 2018 N = 4428 P value n % (95% CI) n % (95% CI) Malaria infection Negative 2773 59.8 (55.6–63.8) 2705 61.1 (56.3–65.7) 0.696 Positive 1867 40.2 (36.2–44.4) 1723 38.9 (34.3–43.7) Gender Male 2312 49.8 (48.0-51.7) 2248 50.8 (48.4–53.1) 0.531 Female 2328 50.2 (48.3–52.0) 2179 49.2 (46.9–51.6) Child’s age in months 6–11 492 10.6 (9.6–11.7) 526 11.9 (10.6–13.2) 0.243 12–23 1073 23.1 (21.9–23.4) 967 21.8 (20.1–23.6) 24–35 1020 22.0 (20.6–24.6) 988 22.3 (20.5–24.2) 36–47 1069 23.0 (21.6–24.6) 953 21.5 (19.9–23.2) 48–59 986 21.3 (19.9–22.7) 994 22.5 (21.0–24.0) Maternal education level No education 1272 30.2 (26.9–33.8) 1005 26.1 (22.2–30.5) 0.062 Primary 2343 55.7 (52.4–58.9) 2085 54.2 (49.6–58.8) Secondary/Higher 595 14.1 (12.2–16.4) 755 19.6 (15.1–25.1) Region North 1775 38.25 (32.9–44.0) 1600 36.2 (29.0–44.0) 0.436 Central 1845 39.8 (34.5–45.3) 2044 46.2 (38.4–54.2) Southern 1020 22.0 (18.4–26.0) 783 17.7 (14.0-22.1) Place of residence Rural 3505 75.5 (71.1–79.5) 3238 73.1 (67.0-78.5) 0.598 Urban 1135 24.5 (20.6–28.9) 1189 26.9 (21.5–33.0) Wealth Index Poorest 1099 23.7 (21.0-26.6) 1058 23.9 (20.0-26.1) 0.989 Poorer 1051 22.6 (20.2–25.3) 1031 23.3 (20.2–26.7) Middle 984 21.2 (18.7–23.9) 913 20.6 (17.6–24.0) Richer 873 18.8 (16.3–21.7) 834 18.8 (15.7–22.4) Richest 633 13.6 (11.3–16.3) 591 13.4 (10.7–16.5) Household has at least one ITN Yes 3353 72.3 (68.9–75.4) 3996 90.2 (87.4–92.5) < 0.001 No 1287 27.7 (24.6–31.1) 432 9.8 (7.5–12.6) Child under 5 slept under LLIN Yes 2110 45.5 (42.4–48.6) 3204 72.4 (69.2–75.3) < 0.001 No 2530 54.5 (51.4–57.7) 1224 27.6 (24.7–30.8) IRS Yes 594 12.8 (10.2–16.0) 680 77.0 (73.1–80.4) < 0.001 No 3987 86.0 (82.6–88.8) 200 22.6 (19.2–26.5) Don’t know 57 1.2 (0.1–1.7) 4 0.4 (0.0-1.2) The overall prevalence of malaria infection was 40% in 2015 and 39% in 2018 (Table 1 ). Changes in malaria infection prevalence were observed in some provinces from 2015 to 2018. In the province of Cabo Delgado, the prevalence of malaria infection increased from 29.4–57.3% while in the province of Zambézia the prevalence of malaria infection decreased from 67.9–44.3% (Fig. 1). Analysis of factors associated with malaria infection among children under 5 years of age As shown in Tables 2 and 3 , in the bivariate analysis of both surveys malaria infection was associated with living in northern or central region, living in rural areas, mother’s low level of education and low household wealth (p < 0.05). No ITN ownership was associated with malaria infection, in the 2015 survey, while age 24–35 months and 48–59 months were associated with malaria infection in the 2018 survey (p < 0.05). Table 2 Logistic regression analysis of factors associated with malaria parasitaemia in children 6–59 months old in Mozambique in 2015 IMASIDA Variable Bi-variable analysis Multivariable analysis OR(95% CI) p-value AOR (95% CI) p-value Gender Male 1 1 Female 0.9 (0.8_1.1) 0.259 1.0(08-1.1) 0.529 Child’s age in months 6–11 1 1 12–23 1.4 (1.1–1.9) 0.018 1.6 (1.1-2.0) 0.015 24–35 1.8 (1.4–2.4) < 0.001 2.1 (1.6–2.9) < 0.001 36–47 1.6 (1.2–2.1) 0.003 1.8 (1.3–2.4) 0.001 48–59 1.7 (1.3–2.3) < 0.001 2.0 (1.5–2.6) < 0.001 Mother’s education level Secondary/Higher 1 1 No education 4.7 (3.0-7.5) < 0.001 1.6 (1.1–2.3) 0.028 Primary 3.7 (2.5–5.4) < 0.001 1.5 (1.1–2.1) 0.007 Region Southern 1 1 North 7.1 (4.6–10.8) < 0.001 3.5 (2.1–5.7) < 0.001 Central 4.3 (2.8–6.6) < 0.001 2.1 (1.3–3.4) 0.002 Location of residence Urban 1 1 Rural 3.7 (2.3–5.9) < 0.001 1.8 (1.1-3.0) 0.022 Wealth index Richest 1 1 Richer 4.0 (2.7-6.0) < 0.001 2.8 (1.8–4.3) < 0.001 Middle 7.6 (4.9–11.9) < 0.001 3.6 (2.1–6.3) < 0.001 Poorer 14.6 (9.2–23.0) < 0.001 5.6 (3.3–9.7) < 0.001 Poorest 19.0 (12.1–29.8) < 0.001 6.8 (4.0-11.8) < 0.001 Household with child < 5 which has at least one ITN Yes 1 1 No 1.5 (1.2–1.9) < 0.001 1.3 (1.0-1.6) 0.033 Child < 5 slept under ITN last night Yes 1 1 No 1.0 (0.8–1.3) 0.854 0.8 (0.7–1.1) 0.140 IRS Yes 1 1 No 1.0 (0.6–1.7) 0.993 0.5 (0.3-1.0) 0.042 Table 3 Logistic regression analysis of factors associated with malaria parasitaemia in children 6–59 months old in Mozambique, MIS 2018. Variable Bi-variable analysis Multivariable analysis OR (95% CI) p-value AOR (95% CI) p-value Gender Male 1 1 Female 0.9 (0.8–1.11) 0.414 1.0 (0.4–1.9) 0.948 Child’s age in months 6–11 1 1 12–23 1.2 (0.8–1.6 0.340 1.3 (0.7–2.4) 0.353 24–35 1.5 (1.2-2.0 0.003 2.1 (1.3–3.5) 0.005 36–47 1.2 (0.9–1.7 0.233 1.6 (0.7–3.3) 0.219 48–59 1.4 (1.1–1.9 0.020 2.1 (1.3–3.6) 0.005 Mother’s education level Secondary/Higher 1 1 No education 6.1 (4.0-9.3) < 0.001 1.1 (0.4–2.9) 0.817 Primary 4.1 (2.9–5.7) < 0.001 1.7 (0.8–3.6) 0.146 Region Southern 1 1 North 5.3 (3.3–8.5) < 0.001 5.6 (2.5–12.9) < 0.001 Central 3.4 (2.2–5.3) < 0.001 4.3 (2.1–9.1) < 0.001 Local of residence Urban 1 1 Rural 3.8 (2.3–6.4) < 0.001 2.3 (1.2–4.5) 0.016 Wealth index Richest 1 1 Richer 8.9 (5.0-15.8) < 0.001 2. 0 (0.8–5.2) 0.135 Middle 24.4 (13.8–43.2) < 0.001 5.0 (2.1–12.0) < 0.001 Poorer 36.0 (19.9–65.1) < 0.001 4.1 (1.8–9.4) < 0.001 Poorest 47.5 (27.1–83.2) < 0.001 5.4 (2.1–13.8) < 0.001 Household with child < 5 which has at list one ITN Yes 1 1 No 1.5 (1.0-2.3) 0.042 0.5 (0.2–1.4) 0.172 Child < 5 slept under ITN last night Yes 1 1 No 0.9 (0.7–1.2) 0.548 1.2 (0.7–1.9) 0.508 IRS Yes 1 1 No 0.9 (0.7–1.4) 0.741 1.0 (0.6–1.5) 0.821 As shown in Table 2 , the results of the 2015 survey multivariate analysis showed that malaria infection was independently associated with children who were 12–23 months old (AOR 1.6; 95% CI: 1.1-2.0), 24–35 months old (AOR 2.1; 95% CI: 1.6–2.9), 36–47 months old (AOR 1.8; 95% CI: 1.3–2.4), 48–59 months old (AOR 2.1; 95% CI: 1.5–2.6), living in the northern region (AOR 3.5; 95% CI: 2.1–5.7) or central region (AOR 2.1; 95% CI: 1.3–3.4), living in rural areas (AOR 1.8; 95% CI: 1.1-3.0), mother with no education (AOR 1.6; 95% CI: 1.1–2.3) or with primary education level (AOR 1.5; 95% CI: 1.1–2.1), no ITN ownership (AOR 1.3; 95% CI: 1.0-1.6) and children living in poor households (p < 0.05). As shown in Table 3 , the results of 2018 survey multivariate analysis showed that malaria infection was independently associated with age 24–35 months (AOR 2.1; 95% CI: 1.3–3.5) or 48–59 months (AOR 2.1; 95% CI: 1.3–3.6); living in the central region (AOR 4.3; 95% CI: 2.1–9.1) or northern region (AOR 5.6; 95% CI: 2.5–12.9); lower household wealth, and living in rural areas (AOR 2.3; 95% CI: 1.2–4.5). Discussion The prevalence of malaria parasitemia in Mozambique remained high between the two surveys, 40% in 2015 and 39% in 2018, despite the significant increase in access to ITNs. These findings are similar to some previous studies in countries with high malaria prevalence that reported no malaria reduction after the increase of interventions for malaria control ( 4 , 5 ). In 2015 the probability of having malaria parasitemia was higher for children living in households with no ITNs, but not in 2018. Previous studies have reported reduction of malaria parasitemia for children living in household with at least one ITN ( 10 , 11 ). Yet the finding in 2018, that showed no impact of ITN ownership with malaria parasitemia prevalence, is consistent with some other works ( 6 , 12 ). Others studies conducted in African countries showed that the increase in the ITN ownership does not directly imply the reduction of malaria parasitaemia ( 5 , 13 , 14 ). There are many possible explanations for this findings, including those related to use. The irregular or inappropriate use of nets and possible exposure of children to mosquito bites during times of day when ITN are not in use could limit their impact ( 6 ). Also not all people who own ITN appropriately use it ( 15 , 16 ) and others authors have attributed it to the lack of caregiver’s knowledge to use ITN as the many reason for increase malaria parasitemia when the coverage of ITN is high ( 17 ). Mosquito insecticide resistance have been reported in Mozambique ( 18 ) which could also limit the effectiveness of ITNs to protect against malaria. This information can provide valuable guidance to the NMCP on the need to implement others control measures ( 6 ). Children older than 12 up to 59 months of age had higher odds of testing positive for malaria in 2015 and in 2018 only children aged 24–35 months and 48–59 months had higher odds of testing positive. These findings are consistent with previous studies ( 8 , 17 , 19 ). As suggested by other authors older children have higher probability of being bitten by mosquitoes when they are playing in the evening while younger children up to 24 months of age may have lower exposure ( 17 ). On the other hand, children in areas of high malaria transmission intensity develop immunity while they grow due to the continuous exposure to infective mosquitoes’ bites. This immunity allow older children to harbour parasites without developing malaria symptoms ( 20 , 21 ). These children with no sterilizing immunity can be a reservoir of parasites and drive malaria transmission Therefore, assessing the prevalence of asymptomatic malaria infections is useful in high transmission areas to guide the designs of interventions for malaria control. Our findings also suggest that other interventions, such as malaria chemoprophylaxis, may be warranted to protect this risk group ( 22 , 23 ). The results from these two surveys showed that children from poorer families were more likely to test positive for malaria parasitemia compared to those from wealthiest families, a finding common across several African countries ( 19 , 24 ). Other studies in African countries have found that children from higher socioeconomic status families were more likely to sleep under ITN compared to those from lower socioeconomic strata ( 25 ). We also found in both surveys that children living in rural areas have higher risk of malaria infection compared to those in urban area ( 26 , 27 ). These results may be explained by previous reports that indicate that rural areas are more suitable breeding grounds for malaria vectors ( 27 ). In addition, in rural areas there is a greater probability of finding precarious housing that facilitates the entry of mosquitoes ( 28 ). The finding that low wealth index and living in rural areas contribute to increase malaria prevalence shows that the interventions to malaria control cannot be isolated, but must involve improving socio-economic status of the population, like improving environment sanitation to avoid mosquitoes breeding and improving house conditions to avoid biting ( 6 ). In 2015, children from mothers with primary level or no education had higher probability of testing positive for malaria parasitemia. Other studies have reported that lower education as risk factor for malaria parasitemia ( 29 ). Mothers with lower education are more likely to develop activities that expose them to mosquito bites and are potentially less informed on how to protect their children from malaria ( 8 ). Limitations Of The Study It is important to note, that data collection for the two surveys was performed at slightly different transmission season. This may can mask the impact of malaria control interventions over the years. Conclusions From 2015 to 2018 the prevalence of malaria parasitemia in children under five years old in Mozambique was stagnant although vector control interventions increased. Our finding show that malaria in Mozambique remains a disease associated to low wealth index and living in rural areas. It suggest that multiple factors like mother’s education, wealth index, area of residence must be considered on malaria control interventions, underscoring the importance of integrated responses that address both the malaria vector and the underlying socioeconomic vulnerabilities that facilitate its spread. Abbreviations AOR – Adjusted Odds Ratio; CI – Confidence Intervals; CNBS – National Bioethics Committee for Health; EA – Enumeration Areas; IMASIDA – Malaria, HIV/AIDS and Immunization Indicator Survey; IRS – Indoor Residual Spaying; ITN – Insecticide Treated Nets; MIS – Malaria Indicator Survey; NMCP – National Malaria Control Program; OR – Odds Ratio; RDT – Rapid Diagnosis Test; RGPH – General Population and Housing Census Declarations Ethics approval and consent to participate The IMASIDA 2015 and MIS 2018 protocols were approved by the ICF Institutional Review Board and the Mozambican National Bioethics Committee. Prior to enrolment, all eligible participants from both surveys provided written informed consent to participate. The consent was obtained from the mother or guardian of a child. The data were analysed anonymously. Consent for publication Not applicable. Availability of data and materials The datasets analysed on this study are available in the DHS Program, [ https://dhsprogram.com/what-we-do/survey-Types/dHs.cfm ]. Competing interests The authors declare that they have no competing interests. Funding The IMASIDA 2015 was funded by USAID through funds from the President’s Malaria Initiative (PMI), Global Fund, WHO, UNICEF, HAI/UW, UNFPA, National Council for Combating HIV and AIDS, through its Common Fund and PEPFAR, through the CDC. The MIS 2018 was funded by USAID through funds from PMI and UNICEF. Authors' contributions SE conceptualization and revision of manuscript; CS writing original manuscript; PA writing and revision of manuscript. AC data analysis and revision of manuscript. BR, AS and BC Revision of manuscript. All authors read and approved the final manuscript. Acknowledgements We would like to thank Eduard Rovira-Vallbona from the Institute of Tropical Medicine, University of Antwerp, Abuchahama Saifodine and Rose Zulliger from US. President’s Malaria Initiative, Mozambique for their constructive comments and technical inputs. References WHO. World Malaria Report 2019. Geneva: World Health Organization, 2019. World Malaria Report; 2019. Ministério da Saúde (MISAU) IN de E (INE) e II (ICFI). Inquérito Demográfico e de Saúde 2011. Calverton, Maryland, USA: MISAU, INE e ICFI. Março, 2012. 2011;1–38: https://dhsprogram.com/pubs/pdf/FR266/FR266.pdf Direcção Nacional de Saúde pública. Plano Estratégico da Malária. 2017;60. Available from: http://www.nationalplanningcycles.org/sites/default/files/country_docs/Mozambique/malaria_plano_estrategico_draftfinal_jan_2012.pdf Mukonka VM, Chanda E, Haque U, Kamuliwo M, Mushinge G, Chileshe J, et al. 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The impact of mass distribution of long lasting insecticide-treated bed-nets on the malaria parasite burden in the Buea Health District in South-West Cameroon: A hospital based chart review of patient’s laboratory records. BMC Res Notes. 2017; 10(1):534. doi:10.1186/s13104-017-2870-8. Jagannathan P, Muhindo MK, Kakuru A, Arinaitwe E, Greenhouse B, Tappero J, et al. Increasing incidence of malaria in children despite insecticide-treated bed nets and prompt anti-malarial therapy in Tororo, Uganda. Malar J. 2012; 11:435. doi.org/10.1186/1475-2875-11-435. Edelu BO, Ikefuna AN, Emodi JI, Adimora GN. Awareness and use of insecticide-treated bed nets among children attending outpatient clinic at UNTH, Enugu - the need for an effective mobilization process. Afr Health Sci. 2010; 10(2):117-119; Tobin-West CI, Alex-Hart BA. Insecticide-treated bednet ownership and utilization in rivers state, Nigeria before a state-wide net distribution campaign. J Vector Borne Dis. 2011; 48(3):133-7. Zgambo M, Mbakaya BC, Kalembo FW. Prevalence and factors associated with malaria parasitaemia in children under the age of five years in Malawi: A comparison study of the 2012 and 2014 Malaria Indicator Surveys (MISs). PLoS One. 2017; Riveron JM, Huijben S, Tchapga W, Tchouakui M, Wondji MJ, Tchoupo M, et al. Escalation of Pyrethroid Resistance in the Malaria Vector Anopheles funestus Induces a Loss of Efficacy of Piperonyl Butoxide-Based Insecticide-Treated Nets in Mozambique. J Infect Dis. 2019; 220(3):467-475.doi: 10.1093/infdis/jiz139. Wanzira H, Katamba H, Okullo AE, Agaba B, Kasule M, Rubahika D. Factors associated with malaria parasitaemia among children under 5 years in Uganda: a secondary data analysis of the 2014 Malaria Indicator Survey dataset. Malar J. 2017; 16(1):191. Griffin JT, Déirdre Hollingsworth T, Reyburn H, Drakeley CJ, Riley EM, Ghani AC. Gradual acquisition of immunity to severe malaria with increasing exposure. Proc R Soc B Biol Sci. 2015; 282(1801):20142657. doi: 10.1098/rspb.2014.2657. Barua P, Beeson JG, Maleta K, Ashorn P, Rogerson SJ. The impact of early life exposure to Plasmodium falciparum on the development of naturally acquired immunity to malaria in young Malawian children. Malar J. 2019; 18(1):11. doi: 10.1186/s12936-019-2647-8. Tizifa TA, Kabaghe AN, McCann RS, van den Berg H, Van Vugt M, Phiri KS. Prevention Efforts for Malaria. Current Tropical Medicine Reports. 2018. 5(1): 41–50. doi: 10.1007/s40475-018-0133-y . Afoakwah C, Deng X, Onur I. Malaria infection among children under-five: The use of large-scale interventions in Ghana. BMC Public Health. 2018; doi.org/10.1186/s12889-018-5428-3. Sonko ST, Jaiteh M, Jafali J, Jarju LBS, D’Alessandro U, Camara A, et al. Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from the Gambia. Malar J. 2014; 13:449. doi: 10.1186/1475-2875-13-449. Ruyange MM, Condo J, Karema C, Binagwaho A, Rukundo A, Muyirukazi Y. Factors associated with the non-use of insecticide-treated nets in Rwandan children. Malar J. 2016; doi:10.1186/s12936-016-1403-6 Liu JX, Bousema T, Zelman B, Gesase S, Hashim R, Maxwell C, et al. Is housing quality associated with malaria incidence among young children and mosquito vector numbers? Evidence from Korogwe, Tanzania. PLoS One. 2014; 9(2): e87358. doi.org/10.1371/journal.pone.0087358. Wang SJ, Lengeler C, Smith TA, Vounatsou P, Diadie DA, Pritroipa X, et al. Rapid urban malaria appraisal (RUMA) I: Epidemiology of urban malaria in Ouagadougou. Malar J. 2005; Wang SJ, Lengeler C, Mtasiwa D, Mshana T, Manane L, Maro G, et al. Rapid Urban Malaria Appraisal (RUMA) II: Epidemiology of urban malaria in Dar es Salaam (Tanzania). Malar J. 2006; 5, 28. doi.org/10.1186/1475-2875-5-28. Degarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub Saharan Africa: A systematic review and meta-analysis. PLoS One. 2019; 14(1):e0211205. doi:10.1371/journal.pone.0211205. 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-168223","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":9832913,"identity":"61c1e87d-693c-4748-92bc-966b10831c6b","order_by":0,"name":"Crizolgo De Jesus Salvador","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYFACxgYGhgIgfYAhAcSVAxEHHhDUYoDQYgzWkkDQJogWMEhsAJH4tPDPPtz84YNBrRzf8YaHD3+21aXPDzv8EGiLnZxuA3YtEucSGwxnGBw3ljxzINmYt+1w7sbbaQZALcnGZgdwOImHsSGZx+BY4oYbCWnSjG0HcjfOTgBpOZC4DY+Ww2At9x+k/wQ5zHB2+gdCWhqbeQxqgLYwpDHwtjEnyEvn4LdF4gxjM+MMgwNAvyQkS/OcO2y4QTqn4ECCAW6/8PewP/7woaIOGGJnEj/+KKuTl5+dvhkoYieHSwsUHAZingSIU8EqDfAqB4E6IGaHmCrfQFD1KBgFo2AUjDAAAD4wZ9FYtZNvAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6313-9999","institution":"​​​​National Institute Health - Mozambique","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Crizolgo","middleName":"De Jesus","lastName":"Salvador","suffix":""},{"id":9832914,"identity":"1f4218e7-4892-4807-9122-39a540a7690f","order_by":1,"name":"Paulo Arnaldo","email":"","orcid":"","institution":"National Institute o Health - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"","lastName":"Arnaldo","suffix":""},{"id":9832915,"identity":"c8678d64-87c2-4da7-87fa-e9f09befb656","order_by":2,"name":"Bernardete Xavier Rafael","email":"","orcid":"","institution":"national Malaria Control Programme - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bernardete","middleName":"Xavier","lastName":"Rafael","suffix":""},{"id":9832916,"identity":"8b8a5f6a-e34b-40b5-8d70-0ad37e7348b2","order_by":3,"name":"Annette Cassy","email":"","orcid":"","institution":"​​​​​​​​​​​National Institute of Health - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Annette","middleName":"","lastName":"Cassy","suffix":""},{"id":9832917,"identity":"6dd4808f-40dc-4b57-a4c4-f83877422ff8","order_by":4,"name":"Baltazar Candrinho","email":"","orcid":"","institution":"national Institute of Health - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Baltazar","middleName":"","lastName":"Candrinho","suffix":""},{"id":9832918,"identity":"dbaf39eb-c5f0-4528-862f-99e9703d9732","order_by":5,"name":"Acácio Sabonete","email":"","orcid":"","institution":"National Institute of Health - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Acácio","middleName":"","lastName":"Sabonete","suffix":""},{"id":9832919,"identity":"822713ee-40b2-4f8e-9236-d3341d95e8cf","order_by":6,"name":"Sónia Enosse","email":"","orcid":"","institution":"National Institute of Health - Mozambique","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sónia","middleName":"","lastName":"Enosse","suffix":""}],"badges":[],"createdAt":"2021-01-28 06:24:49","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-168223/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-168223/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":5601455,"identity":"0a65cbd4-f8dd-4c54-8d0e-fc84f1bdfd08","added_by":"auto","created_at":"2021-02-04 00:33:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":50462,"visible":true,"origin":"","legend":"Distribution of malaria prevalence in children 6-59 months old in Mozambique by province, 2015 and 2018","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-168223/v1/8e6faea2db09f5978a9ba212.png"},{"id":13655557,"identity":"907201fd-9df8-47bb-870d-c63317f32340","added_by":"auto","created_at":"2021-09-17 10:02:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":487479,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-168223/v1/e22e9da7-10d6-40aa-abad-39160fbbcf2d.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eFactors Associated with Prevalence of Malaria Infection among Children under 5 Years of Age in Mozambique: 2015 vs 2018\u003c/p\u003e","fulltext":[{"header":"Background","content":" \u003cp\u003eMalaria is still a leading cause of morbidity and mortality among children under five years of age around the world. In 2018, 228\u0026nbsp;million cases and 405,000 deaths from malaria were reported globally. The sub-Saharan Africa region accounted for 93% of the cases and 94% of the deaths. Mozambique contributed4% of the global malaria case burden (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The distribution of malaria prevalence in Mozambique is heterogeneous, with a higher prevalence in the northern and central regions compared to the southern region (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The National Malaria Control Program (NMCP) of Mozambique developed the 2017\u0026ndash;2022 National Strategic Plan to implement and monitor interventions for malaria control. In order to reduce the burden of malaria in the country, the NMCP is investing resources in a combination of vector control and case management interventions (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, the impact of the interventions on high risk populations and areas of high prevalence is not yet known. Understanding the factors associated with the prevalence of malaria infection and its distribution is important to improve the planning of national and sub-national malaria control strategies.\u003c/p\u003e \u003cp\u003ePrevious global research on the factors associated with malaria prevalence and distribution have shown varied results. Some studies have shown that access and use of prevention strategies such as insecticide treated nets (ITNs) and indoor residual spray (IRS) reduced malaria prevalence (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) while in others the use of these strategies have shown no significant impact(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Higher socioeconomic and educational status have also been indicated as protective by some authors (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) while others found no relation (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In this analysis we sought to determine the prevalence of malaria infections and its predictors among children six to fifty-nine months old in Mozambique by comparing the 2015 Malaria, HIV/AIDS, and Immunization Indicator Survey (IMASIDA) and the 2018 Malaria Indicator Survey (MIS). The analysis will provide information on the coverage of interventions for malaria control and factors associated to the prevalence of malaria. These information can support the NMCP to strengthen the planning malaria control interventions.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy setting\u003c/h2\u003e \u003cp\u003eThe analysis is based on two nation-wide surveys. Mozambique is divided in three regions, northern, central, and southern. The northern region includes the provinces of Niassa, Cabo Delgado and Nampula, and the central region includes the provinces of Tete, Zamb\u0026eacute;zia, Manica and Sofala, and the southern region includes the provinces of Inhambane, Gaza, Maputo and Maputo City. Typically, Mozambique has a tropical climate with two distinct seasons: a hot and humid season from October to March and a dry and cool season from April to September, although there are variations depending on the region and altitude. Malaria transmission is higher in the hot and humid season due to the abundance of water and vegetation, which favours breeding of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes. \u003cem\u003eP. falciparum\u003c/em\u003e accounts for 90% of all malaria infections (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and data source\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective analysis of data from two community-based surveys conducted in 2015 and 2018. The IMASIDA was conducted from June to September in 2015, while the MIS was conducted from March to June 2018. For both surveys, the sampling was representative nationally, for rural and urban areas, and at the provincial level. Households were selected using data from the General Population and Housing Census 2007 (RGPH 2007). In the first stage of sampling, Enumeration Areas (EAs) were selected from the total EA outlined in the RGPH 2007, with probability-proportional-to-size, in which some were located in urban areas and others in rural areas. A total of 307 EAs, in which 134 (43.6%) were urban, were selected for the IMASIDA 2015 and 224 EAs, in which 92 (41.1%) were urban, were selected for the MIS 2018. In the second sampling stage, all households within the EA were listed followed by random selection of households. A total of 24 and 28 households per EA were selected for the IMASIDA 2015 and for the MIS 2018, respectively. In total, 7,368 households were selected in IMASIDA 2015 and 6,279 households were selected in MIS 2018. Women aged 15\u0026ndash;49 years and children aged 6\u0026ndash;59 months, who were habitually resident or had spent the night before the survey in the household were eligible for interview and malaria testing respectively. For the IMASIDA, responses rates were 97.6% for selected households and 94.5% for eligible women; for the MIS 2018, response rates were 99.0% for households and 98.3% for eligible women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eFor both surveys data was collected from three sources: i) a household questionnaire was used to collect information to determine the household wealth index, information of the household owner-ship and use of insecticide treated nets (ITN), and exposure to indoor residual spraying (IRS); ii) a questionnaire addressed to women aged 15\u0026ndash;49 was used to collect information on age, residence history, educational level, intermittent preventive treatment of malaria during pregnancy, use of ITN, treatment of malaria in children under 5 years of age and knowledge of malaria; iii) a biomarkers questionnaire was used to record the results of the malaria and anaemia tests in children 6\u0026ndash;59 months of age.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMalaria testing\u003c/h2\u003e \u003cp\u003eMalaria tests were performed using capillary blood samples taken from the fingers or heels of included children. In the IMASIDA 2015, malaria testing was performed using rapid diagnosis test (RDT) SD Bioline Malaria Ag Pf and Pv (Abbott) to detect \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP.vivax\u003c/em\u003e antigens while in the MIS 2018 the RDT was SD Bioline Malaria Ag Pf (Abbott) which detects only the \u003cem\u003eP. falciparum\u003c/em\u003e antigen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo prepare the data for analysis, the individual members (PR) datasets from both surveys were merged into one dataset. Special (svy) survey commands were used to account for complex multilevel survey design. Data were weighted to account for the differential selection probabilities at the EA, household and individual levels. Only weighted survey data are presented in this manuscript. Socio-economic, demographic and vector control characteristics were compared between 2015 and 2018 using \u003cem\u003et-student\u003c/em\u003e test. Logistic regression was used to evaluate factors associated with presence of \u003cem\u003ePlasmodium sp\u003c/em\u003e antigen as detected by RDT among children under 5 years of age (dependent variable). The independent variables included: age; gender; residence (urban vs rural); region (southern, central or northern); use of ITNs; IRS in the past 6 months; highest education level attained by the mother; and wealth index. Multivariate complex sampling logistic regression was used to identify factors associated with malaria infection, with estimated adjusted odds ratio (AOR) and respective 95% confidence intervals (CI). All statistical analyses were performed using Stata, version 15 (Stata Corporation, College Station, Texas).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003eFor both surveys, ethical approval was obtained from the Mozambique National Bioethics Committee for Health (CNBS) prior to data collection, IMASIDA 2015 (42/CNBS/2014) and MIS 2018 (69/CNBS/18). Written informed consent was obtained from study participants. Parental consent was also provided for all children who were tested for malaria and anaemia.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eGeneral characteristics of study participants and prevalence of malaria infection\u003c/h2\u003e\n\u003cp\u003eA total of 9,068 children under the age of five years were tested for malaria infection, of which 4,640 (51.2%) from the 2015 survey and 4,428 (48.8%) from the 2018 survey. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the socio-demographic characteristics of study participants for both surveys; no significant differences were found. The proportion of households who owned at least one ITN was significantly higher in 2018, with 72.3% in 2015 and 90.2% in 2018 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, the proportion of children under 5 years who reported sleeping under ITN the night before the survey increased from45.5% in 2015 to 72.4% in 2018 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eDemographic characteristics of children 6\u0026ndash;59 months old and vector control interventions indicators in two surveys in Mozambique, 2015 and 2018.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eIMASIDA 2015\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;4640\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMIS 2018\u003c/p\u003e\n\u003cp\u003eN\u0026thinsp;=\u0026thinsp;4428\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003en\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e% (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003en\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e% (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eMalaria infection\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNegative\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2773\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59.8 (55.6\u0026ndash;63.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2705\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61.1 (56.3\u0026ndash;65.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.696\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePositive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1867\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.2 (36.2\u0026ndash;44.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1723\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38.9 (34.3\u0026ndash;43.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2312\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.8 (48.0-51.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.8 (48.4\u0026ndash;53.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.531\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2328\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e50.2 (48.3\u0026ndash;52.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2179\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.2 (46.9\u0026ndash;51.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eChild\u0026rsquo;s age in months\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u0026ndash;11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e492\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.6 (9.6\u0026ndash;11.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e526\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11.9 (10.6\u0026ndash;13.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003e0.243\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u0026ndash;23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1073\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.1 (21.9\u0026ndash;23.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e967\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.8 (20.1\u0026ndash;23.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u0026ndash;35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.0 (20.6\u0026ndash;24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e988\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.3 (20.5\u0026ndash;24.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u0026ndash;47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1069\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.0 (21.6\u0026ndash;24.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e953\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.5 (19.9\u0026ndash;23.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u0026ndash;59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e986\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.3 (19.9\u0026ndash;22.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e994\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.5 (21.0\u0026ndash;24.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eMaternal education level\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.2 (26.9\u0026ndash;33.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.1 (22.2\u0026ndash;30.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e0.062\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2343\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.7 (52.4\u0026ndash;58.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2085\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.2 (49.6\u0026ndash;58.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary/Higher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e595\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14.1 (12.2\u0026ndash;16.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e755\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.6 (15.1\u0026ndash;25.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eRegion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNorth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1775\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e38.25 (32.9\u0026ndash;44.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.2 (29.0\u0026ndash;44.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e0.436\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCentral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1845\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e39.8 (34.5\u0026ndash;45.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46.2 (38.4\u0026ndash;54.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSouthern\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.0 (18.4\u0026ndash;26.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e783\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.7 (14.0-22.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003ePlace of residence\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3505\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75.5 (71.1\u0026ndash;79.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3238\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e73.1 (67.0-78.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.598\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1135\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.5 (20.6\u0026ndash;28.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26.9 (21.5\u0026ndash;33.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eWealth Index\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1099\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.7 (21.0-26.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.9 (20.0-26.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"5\" align=\"left\"\u003e\n\u003cp\u003e0.989\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1051\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.6 (20.2\u0026ndash;25.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.3 (20.2\u0026ndash;26.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMiddle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e984\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21.2 (18.7\u0026ndash;23.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e913\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.6 (17.6\u0026ndash;24.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRicher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e873\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.8 (16.3\u0026ndash;21.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e834\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.8 (15.7\u0026ndash;22.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRichest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e633\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.6 (11.3\u0026ndash;16.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e591\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13.4 (10.7\u0026ndash;16.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eHousehold has at least one ITN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3353\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72.3 (68.9\u0026ndash;75.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3996\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e90.2 (87.4\u0026ndash;92.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1287\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.7 (24.6\u0026ndash;31.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e432\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.8 (7.5\u0026ndash;12.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eChild under 5 slept under LLIN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2110\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45.5 (42.4\u0026ndash;48.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3204\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e72.4 (69.2\u0026ndash;75.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2530\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.5 (51.4\u0026ndash;57.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1224\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27.6 (24.7\u0026ndash;30.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" align=\"left\"\u003e\n\u003cp\u003eIRS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e594\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12.8 (10.2\u0026ndash;16.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e680\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77.0 (73.1\u0026ndash;80.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3987\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e86.0 (82.6\u0026ndash;88.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e200\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22.6 (19.2\u0026ndash;26.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (0.1\u0026ndash;1.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4 (0.0-1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe overall prevalence of malaria infection was 40% in 2015 and 39% in 2018 (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Changes in malaria infection prevalence were observed in some provinces from 2015 to 2018. In the province of Cabo Delgado, the prevalence of malaria infection increased from 29.4\u0026ndash;57.3% while in the province of Zamb\u0026eacute;zia the prevalence of malaria infection decreased from 67.9\u0026ndash;44.3% (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003eAnalysis of factors associated with malaria infection among children under 5 years of age\u003c/h2\u003e\n\u003cp\u003eAs shown in Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, in the bivariate analysis of both surveys malaria infection was associated with living in northern or central region, living in rural areas, mother\u0026rsquo;s low level of education and low household wealth (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). No ITN ownership was associated with malaria infection, in the 2015 survey, while age 24\u0026ndash;35 months and 48\u0026ndash;59 months were associated with malaria infection in the 2018 survey (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLogistic regression analysis of factors associated with malaria parasitaemia in children 6\u0026ndash;59 months old in Mozambique in 2015 IMASIDA\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBi-variable analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMultivariable analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e0.9 (0.8_1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.259\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0(08-1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.529\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u0026rsquo;s age in months\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u0026ndash;11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u0026ndash;23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.4 (1.1\u0026ndash;1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.018\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6 (1.1-2.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u0026ndash;35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.8 (1.4\u0026ndash;2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1 (1.6\u0026ndash;2.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u0026ndash;47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.6 (1.2\u0026ndash;2.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (1.3\u0026ndash;2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u0026ndash;59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.7 (1.3\u0026ndash;2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.0 (1.5\u0026ndash;2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMother\u0026rsquo;s education level\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary/Higher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4.7 (3.0-7.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6 (1.1\u0026ndash;2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.7 (2.5\u0026ndash;5.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5 (1.1\u0026ndash;2.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRegion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSouthern\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNorth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e7.1 (4.6\u0026ndash;10.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.5 (2.1\u0026ndash;5.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCentral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4.3 (2.8\u0026ndash;6.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1 (1.3\u0026ndash;3.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLocation of residence\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3.7 (2.3\u0026ndash;5.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8 (1.1-3.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWealth index\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRichest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRicher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4.0 (2.7-6.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.8 (1.8\u0026ndash;4.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMiddle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e7.6 (4.9\u0026ndash;11.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.6 (2.1\u0026ndash;6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e14.6 (9.2\u0026ndash;23.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6 (3.3\u0026ndash;9.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e19.0 (12.1\u0026ndash;29.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8 (4.0-11.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold with child\u0026thinsp;\u0026lt;\u0026thinsp;5 which has at least one ITN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.5 (1.2\u0026ndash;1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3 (1.0-1.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.033\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u0026thinsp;\u0026lt;\u0026thinsp;5 slept under ITN last night\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.0 (0.8\u0026ndash;1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8 (0.7\u0026ndash;1.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.140\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIRS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1.0 (0.6\u0026ndash;1.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.993\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5 (0.3-1.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eLogistic regression analysis of factors associated with malaria parasitaemia in children 6\u0026ndash;59 months old in Mozambique, MIS 2018.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBi-variable analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMultivariable analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAOR (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eGender\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9 (0.8\u0026ndash;1.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.414\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0 (0.4\u0026ndash;1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.948\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u0026rsquo;s age in months\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u0026ndash;11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12\u0026ndash;23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (0.8\u0026ndash;1.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.340\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.3 (0.7\u0026ndash;2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.353\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24\u0026ndash;35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5 (1.2-2.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.003\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1 (1.3\u0026ndash;3.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36\u0026ndash;47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (0.9\u0026ndash;1.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.233\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6 (0.7\u0026ndash;3.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.219\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48\u0026ndash;59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.4 (1.1\u0026ndash;1.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.020\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1 (1.3\u0026ndash;3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMother\u0026rsquo;s education level\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary/Higher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo education\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.1 (4.0-9.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.1 (0.4\u0026ndash;2.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.817\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.1 (2.9\u0026ndash;5.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.7 (0.8\u0026ndash;3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.146\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRegion\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSouthern\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNorth\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.3 (3.3\u0026ndash;8.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.6 (2.5\u0026ndash;12.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCentral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.4 (2.2\u0026ndash;5.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.3 (2.1\u0026ndash;9.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLocal of residence\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.8 (2.3\u0026ndash;6.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.3 (1.2\u0026ndash;4.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.016\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eWealth index\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRichest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRicher\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.9 (5.0-15.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2. 0 (0.8\u0026ndash;5.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.135\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMiddle\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.4 (13.8\u0026ndash;43.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.0 (2.1\u0026ndash;12.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorer\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.0 (19.9\u0026ndash;65.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.1 (1.8\u0026ndash;9.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePoorest\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47.5 (27.1\u0026ndash;83.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.4 (2.1\u0026ndash;13.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHousehold with child\u0026thinsp;\u0026lt;\u0026thinsp;5 which has at list one ITN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.5 (1.0-2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5 (0.2\u0026ndash;1.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.172\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChild\u0026thinsp;\u0026lt;\u0026thinsp;5 slept under ITN last night\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9 (0.7\u0026ndash;1.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.548\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.2 (0.7\u0026ndash;1.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.508\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIRS\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.9 (0.7\u0026ndash;1.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.741\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0 (0.6\u0026ndash;1.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.821\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, the results of the 2015 survey multivariate analysis showed that malaria infection was independently associated with children who were 12\u0026ndash;23 months old (AOR 1.6; 95% CI: 1.1-2.0), 24\u0026ndash;35 months old (AOR 2.1; 95% CI: 1.6\u0026ndash;2.9), 36\u0026ndash;47 months old (AOR 1.8; 95% CI: 1.3\u0026ndash;2.4), 48\u0026ndash;59 months old (AOR 2.1; 95% CI: 1.5\u0026ndash;2.6), living in the northern region (AOR 3.5; 95% CI: 2.1\u0026ndash;5.7) or central region (AOR 2.1; 95% CI: 1.3\u0026ndash;3.4), living in rural areas (AOR 1.8; 95% CI: 1.1-3.0), mother with no education (AOR 1.6; 95% CI: 1.1\u0026ndash;2.3) or with primary education level (AOR 1.5; 95% CI: 1.1\u0026ndash;2.1), no ITN ownership (AOR 1.3; 95% CI: 1.0-1.6) and children living in poor households (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the results of 2018 survey multivariate analysis showed that malaria infection was independently associated with age 24\u0026ndash;35 months (AOR 2.1; 95% CI: 1.3\u0026ndash;3.5) or 48\u0026ndash;59 months (AOR 2.1; 95% CI: 1.3\u0026ndash;3.6); living in the central region (AOR 4.3; 95% CI: 2.1\u0026ndash;9.1) or northern region (AOR 5.6; 95% CI: 2.5\u0026ndash;12.9); lower household wealth, and living in rural areas (AOR 2.3; 95% CI: 1.2\u0026ndash;4.5).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eThe prevalence of malaria parasitemia in Mozambique remained high between the two surveys, 40% in 2015 and 39% in 2018, despite the significant increase in access to ITNs. These findings are similar to some previous studies in countries with high malaria prevalence that reported no malaria reduction after the increase of interventions for malaria control (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 2015 the probability of having malaria parasitemia was higher for children living in households with no ITNs, but not in 2018. Previous studies have reported reduction of malaria parasitemia for children living in household with at least one ITN (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Yet the finding in 2018, that showed no impact of ITN ownership with malaria parasitemia prevalence, is consistent with some other works (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Others studies conducted in African countries showed that the increase in the ITN ownership does not directly imply the reduction of malaria parasitaemia (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). There are many possible explanations for this findings, including those related to use. The irregular or inappropriate use of nets and possible exposure of children to mosquito bites during times of day when ITN are not in use could limit their impact (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Also not all people who own ITN appropriately use it (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) and others authors have attributed it to the lack of caregiver\u0026rsquo;s knowledge to use ITN as the many reason for increase malaria parasitemia when the coverage of ITN is high (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Mosquito insecticide resistance have been reported in Mozambique (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) which could also limit the effectiveness of ITNs to protect against malaria. This information can provide valuable guidance to the NMCP on the need to implement others control measures (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChildren older than 12 up to 59 months of age had higher odds of testing positive for malaria in 2015 and in 2018 only children aged 24\u0026ndash;35 months and 48\u0026ndash;59 months had higher odds of testing positive. These findings are consistent with previous studies (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). As suggested by other authors older children have higher probability of being bitten by mosquitoes when they are playing in the evening while younger children up to 24 months of age may have lower exposure (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). On the other hand, children in areas of high malaria transmission intensity develop immunity while they grow due to the continuous exposure to infective mosquitoes\u0026rsquo; bites. This immunity allow older children to harbour parasites without developing malaria symptoms (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). These children with no sterilizing immunity can be a reservoir of parasites and drive malaria transmission Therefore, assessing the prevalence of asymptomatic malaria infections is useful in high transmission areas to guide the designs of interventions for malaria control. Our findings also suggest that other interventions, such as malaria chemoprophylaxis, may be warranted to protect this risk group (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results from these two surveys showed that children from poorer families were more likely to test positive for malaria parasitemia compared to those from wealthiest families, a finding common across several African countries (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Other studies in African countries have found that children from higher socioeconomic status families were more likely to sleep under ITN compared to those from lower socioeconomic strata (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). We also found in both surveys that children living in rural areas have higher risk of malaria infection compared to those in urban area (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). These results may be explained by previous reports that indicate that rural areas are more suitable breeding grounds for malaria vectors (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). In addition, in rural areas there is a greater probability of finding precarious housing that facilitates the entry of mosquitoes (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The finding that low wealth index and living in rural areas contribute to increase malaria prevalence shows that the interventions to malaria control cannot be isolated, but must involve improving socio-economic status of the population, like improving environment sanitation to avoid mosquitoes breeding and improving house conditions to avoid biting (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 2015, children from mothers with primary level or no education had higher probability of testing positive for malaria parasitemia. Other studies have reported that lower education as risk factor for malaria parasitemia (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Mothers with lower education are more likely to develop activities that expose them to mosquito bites and are potentially less informed on how to protect their children from malaria (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e "},{"header":"Limitations Of The Study","content":" \u003cp\u003eIt is important to note, that data collection for the two surveys was performed at slightly different transmission season. This may can mask the impact of malaria control interventions over the years.\u003c/p\u003e "},{"header":"Conclusions","content":" \u003cp\u003eFrom 2015 to 2018 the prevalence of malaria parasitemia in children under five years old in Mozambique was stagnant although vector control interventions increased. Our finding show that malaria in Mozambique remains a disease associated to low wealth index and living in rural areas. It suggest that multiple factors like mother\u0026rsquo;s education, wealth index, area of residence must be considered on malaria control interventions, underscoring the importance of integrated responses that address both the malaria vector and the underlying socioeconomic vulnerabilities that facilitate its spread.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eAOR \u0026ndash; Adjusted Odds Ratio; CI \u0026ndash; Confidence Intervals; CNBS \u0026ndash; National Bioethics Committee for Health; EA \u0026ndash; Enumeration Areas; IMASIDA \u0026ndash; Malaria, HIV/AIDS and Immunization Indicator Survey; IRS \u0026ndash; Indoor Residual Spaying; ITN \u0026ndash; Insecticide Treated Nets; MIS \u0026ndash; Malaria Indicator Survey; NMCP \u0026ndash; National Malaria Control Program; OR \u0026ndash; Odds Ratio; RDT \u0026ndash; Rapid Diagnosis Test; RGPH \u0026ndash; General Population and Housing Census\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe IMASIDA 2015 and MIS 2018 protocols were approved by the ICF Institutional Review Board and the Mozambican National Bioethics Committee. Prior to enrolment, all eligible participants from both surveys provided written informed consent to participate. The consent was obtained from the mother or guardian of a child. The data were analysed anonymously.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets analysed on this study are available in the DHS Program, [\u003ca href=\"https://dhsprogram.com/what-we-do/survey-Types/dHs.cfm\"\u003ehttps://dhsprogram.com/what-we-do/survey-Types/dHs.cfm\u003c/a\u003e].\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe IMASIDA 2015 was funded by USAID through funds from the President\u0026rsquo;s Malaria Initiative (PMI), Global Fund, WHO, UNICEF, HAI/UW, UNFPA, National Council for Combating HIV and AIDS, through its Common Fund and PEPFAR, through the CDC. The MIS 2018 was funded by USAID through funds from PMI and UNICEF.\u003c/p\u003e\n\u003ch2\u003eAuthors' contributions\u003c/h2\u003e\n\u003cp\u003eSE conceptualization and revision of manuscript; CS writing original manuscript; PA writing and revision of manuscript. AC data analysis and revision of manuscript. BR, AS and BC Revision of manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe would like to thank Eduard Rovira-Vallbona from the Institute of Tropical Medicine, University of Antwerp, Abuchahama Saifodine and Rose Zulliger from US. President\u0026rsquo;s Malaria Initiative, Mozambique for their constructive comments and technical inputs.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWHO. World Malaria Report 2019. Geneva: World Health Organization, 2019. World Malaria Report; 2019.\u003c/li\u003e\n\u003cli\u003eMinist\u0026eacute;rio da Sa\u0026uacute;de (MISAU) IN de E (INE) e II (ICFI). Inqu\u0026eacute;rito Demogr\u0026aacute;fico e de Sa\u0026uacute;de 2011. Calverton, Maryland, USA: MISAU, INE e ICFI. Mar\u0026ccedil;o, 2012. 2011;1\u0026ndash;38: https://dhsprogram.com/pubs/pdf/FR266/FR266.pdf\u003c/li\u003e\n\u003cli\u003eDirec\u0026ccedil;\u0026atilde;o Nacional de Sa\u0026uacute;de p\u0026uacute;blica. Plano Estrat\u0026eacute;gico da Mal\u0026aacute;ria. 2017;60. Available from: http://www.nationalplanningcycles.org/sites/default/files/country_docs/Mozambique/malaria_plano_estrategico_draftfinal_jan_2012.pdf\u003c/li\u003e\n\u003cli\u003eMukonka VM, Chanda E, Haque U, Kamuliwo M, Mushinge G, Chileshe J, et al. High burden of malaria following scale-up of control interventions in Nchelenge District, Luapula Province, Zambia. Malar J. 2014; 13:153. doi.org/10.1186/1475-2875-13-153.\u003c/li\u003e\n\u003cli\u003eLouis VR, Schoeps A, Tiendreb\u0026eacute;ogo J, Beiersmann C, Y\u0026eacute; M, Damiba MR, et al. An insecticide-treated bed-net campaign and childhood malaria in burkina faso. Bull World Health Organ. 2015; 93(11):750-758. doi:10.2471/BLT.14.147702.\u003c/li\u003e\n\u003cli\u003eRoberts D, Matthews G. Risk factors of malaria in children under the age of five years old in Uganda. Malar J. 2016; 15:246.doi.org/10.1186/s12936-016-1290-x.\u003c/li\u003e\n\u003cli\u003eDonnelly B, Berrang-Ford L, Labb\u0026eacute; J, Twesigomwe S, Lwasa S, Namanya DB, et al. Plasmodium falciparum malaria parasitaemia among indigenous Batwa and non-indigenous communities of Kanungu district, Uganda. Malar J. 2016; 15:254. doi.org/10.1186/s12936-016-1299-1.\u003c/li\u003e\n\u003cli\u003eM K, W T, M T, E T, M A. Factors Associated with Malaria Prevalence among Children under Five Years in the Hohoe Municipality of Ghana. J Transm Dis Immun. 2017; 1:2.\u003c/li\u003e\n\u003cli\u003eMISAU-PNCM. Relat\u0026oacute;rio Anual do Programa Nacional de Controlo da Mal\u0026aacute;ria (2017). Direc\u0026ccedil;\u0026atilde;o Nacional de Sa\u0026uacute;de P\u0026uacute;blica, Maputo, Mo\u0026ccedil;ambique. 2017.\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e\n\u003col start=\"10\"\u003e\n\u003cli\u003eKyu HH, Georgiades K, Shannon HS, Boyle MH. Evaluation of the association between long-lasting insecticidal nets mass distribution campaigns and child malaria in Nigeria. Malar J. 2013; 12: 14. doi.org/10.1186/1475-2875-12-14.\u003c/li\u003e\n\u003cli\u003eAtieli HE, Zhou G, Afrane Y, Lee MC, Mwanzo I, Githeko AK, et al. Insecticide-treated net (ITN) ownership, usage, and malaria transmission in the highlands of western Kenya. Parasites and Vectors. 2011; 4, 113. doi.org/10.1186/1756-3305-4-113.\u003c/li\u003e\n\u003cli\u003eByakika-Kibwika P, Ndeezi G, Kamya MR. Health care related factors associated with severe malaria in children in Kampala, Uganda. Afr Health Sci. 2009; 9(3):206-210.\u003c/li\u003e\n\u003cli\u003eYekabong RC, Ebile WA, Fon PN, Asongalem EA. The impact of mass distribution of long lasting insecticide-treated bed-nets on the malaria parasite burden in the Buea Health District in South-West Cameroon: A hospital based chart review of patient\u0026rsquo;s laboratory records. BMC Res Notes. 2017; 10(1):534. doi:10.1186/s13104-017-2870-8.\u003c/li\u003e\n\u003cli\u003eJagannathan P, Muhindo MK, Kakuru A, Arinaitwe E, Greenhouse B, Tappero J, et al. Increasing incidence of malaria in children despite insecticide-treated bed nets and prompt anti-malarial therapy in Tororo, Uganda. Malar J. 2012; 11:435. doi.org/10.1186/1475-2875-11-435.\u003c/li\u003e\n\u003cli\u003eEdelu BO, Ikefuna AN, Emodi JI, Adimora GN. Awareness and use of insecticide-treated bed nets among children attending outpatient clinic at UNTH, Enugu - the need for an effective mobilization process. Afr Health Sci. 2010; 10(2):117-119;\u003c/li\u003e\n\u003cli\u003eTobin-West CI, Alex-Hart BA. Insecticide-treated bednet ownership and utilization in rivers state, Nigeria before a state-wide net distribution campaign. J Vector Borne Dis. 2011; 48(3):133-7.\u003c/li\u003e\n\u003cli\u003eZgambo M, Mbakaya BC, Kalembo FW. Prevalence and factors associated with malaria parasitaemia in children under the age of five years in Malawi: A comparison study of the 2012 and 2014 Malaria Indicator Surveys (MISs). PLoS One. 2017;\u003c/li\u003e\n\u003cli\u003eRiveron JM, Huijben S, Tchapga W, Tchouakui M, Wondji MJ, Tchoupo M, et al. Escalation of Pyrethroid Resistance in the Malaria Vector Anopheles funestus Induces a Loss of Efficacy of Piperonyl Butoxide-Based Insecticide-Treated Nets in Mozambique. 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Factors associated with the non-use of insecticide-treated nets in Rwandan children. Malar J. 2016; doi:10.1186/s12936-016-1403-6\u003c/li\u003e\n\u003cli\u003eLiu JX, Bousema T, Zelman B, Gesase S, Hashim R, Maxwell C, et al. Is housing quality associated with malaria incidence among young children and mosquito vector numbers? Evidence from Korogwe, Tanzania. PLoS One. 2014; 9(2): e87358. doi.org/10.1371/journal.pone.0087358.\u003c/li\u003e\n\u003cli\u003eWang SJ, Lengeler C, Smith TA, Vounatsou P, Diadie DA, Pritroipa X, et al. Rapid urban malaria appraisal (RUMA) I: Epidemiology of urban malaria in Ouagadougou. Malar J. 2005;\u003c/li\u003e\n\u003cli\u003eWang SJ, Lengeler C, Mtasiwa D, Mshana T, Manane L, Maro G, et al. Rapid Urban Malaria Appraisal (RUMA) II: Epidemiology of urban malaria in Dar es Salaam (Tanzania). Malar J. 2006; 5, 28. doi.org/10.1186/1475-2875-5-28.\u003c/li\u003e\n\u003cli\u003eDegarege A, Fennie K, Degarege D, Chennupati S, Madhivanan P. Improving socioeconomic status may reduce the burden of malaria in sub Saharan Africa: A systematic review and meta-analysis. PLoS One. 2019; 14(1):e0211205. doi:10.1371/journal.pone.0211205.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","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, P. falciparum, children six to 59 months old, insecticide treated nets, Mozambique","lastPublishedDoi":"10.21203/rs.3.rs-168223/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-168223/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMalaria is still a leading cause of morbidity and mortality among children under five years old in Mozambique. In this study we sought to determine the prevalence of malaria infection and its predictors among children six to 59 months old in Mozambique.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eData from two national malaria indicators surveys in 2015 and 2018 were compared. In both surveys, blood samples were collected among children six to 59 months old to detect \u003cem\u003ePlasmodium falciparum\u003c/em\u003e antigen by a rapid diagnostic test, and questionnaires were applied to collect socio-economic, demographic and vector control data from their households. Association of malaria rapid diagnostic test positivity with age, gender, residence, region, use of a vector control intervention, mother’s level of education and wealth index was assessed by logistic regression, using both univariate and multivariate analysis. A complex sampling logistic regression model was used to identify factors associated with malaria infection with estimated adjusted odds ratio and respective 95% confidence intervals. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 9,068 children were tested for malaria infection of which 4,640 were in 2015 and 4,428 in 2018. The prevalence of malaria infection was 40.2% and 38.9% in 2015 and 2018, respectively. From 2015 to 2018, insecticide-treated nets ownership increased from 72.3% to 90.2% (p\u0026lt;0.001) and insecticide-treated nets use increased from 45.5% to 72.4% in children under the age of 5 years (p\u0026lt;0.001). In multivariate analysis, malaria infection was associated with region (north and central regions) and rural area for both surveys. Living in households with a wealth quintile lower than the wealthiest was associated with an increased odds of malaria infection (p\u0026lt;0.001). Maternal level of education and absence of an insecticide-treated net in the household were associated with malaria infection in 2015 (p\u0026lt;0.001) but not in 2018. Malaria infection was associated with age older than 12 months in 2015 and with age 24-35 months and 48-59 months in2018. \u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003cstrong\u003eConclusions: \u003c/strong\u003eAlthough insecticide-treated nets ownership and use have increased between the two surveys, prevalence of malaria infection remained stagnant. The main predictors of malaria infection were region, place of residence and socioeconomic status, underscoring the importance of broader developmental and socioeconomic factors on malaria prevalence.\u003c/p\u003e","manuscriptTitle":"Factors Associated with Prevalence of Malaria Infection among Children under 5 Years of Age in Mozambique: 2015 vs 2018","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-02-04 00:33:53","doi":"10.21203/rs.3.rs-168223/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":"a208049d-9223-49ac-850c-d6c51c9f4ff5","owner":[],"postedDate":"February 4th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":2204812,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-03-04T16:59:18+00:00","versionOfRecord":[],"versionCreatedAt":"2021-02-04 00:33:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-168223","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-168223","identity":"rs-168223","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}