Gender difference in the incidence of malaria diagnosed at public health facilities in Uganda.

BACKGROUND: Routine malaria surveillance data in Africa primarily come from public health facilities reporting to national health management information systems. Although information on gender is routinely collected from patients presenting to these health facilities, stratification of malaria surveillance data by gender is rarely done. This study evaluated gender difference among patients diagnosed with parasitological confirmed malaria at public health facilities in Uganda. METHODS: This study utilized individual level patient data collected from January 2020 through April 2021 at 12 public health facilities in Uganda and cross-sectional surveys conducted in target areas around these facilities in April 2021. Associations between gender and the incidence of malaria and non-malarial visits captured at the health facilities from patients residing within the target areas were estimated using poisson regression models controlling for seasonality. Associations between gender and data on health-seeking behaviour from the cross-sectional surveys were estimated using poisson regression models controlling for seasonality. RESULTS: Overall, incidence of malaria diagnosed per 1000 person years was 735 among females and 449 among males (IRR = 1.72, 95% CI 1.68-1.77, p < 0.001), with larger differences among those 15-39 years (IRR = 2.46, 95% CI 2.34-2.58, p < 0.001) and over 39 years (IRR = 2.26, 95% CI 2.05-2.50, p < 0.001) compared to those under 15 years (IRR = 1.46, 95% CI 1.41-1.50, p < 0.001). Female gender was also associated with a higher incidence of visits where malaria was not suspected (IRR = 1.77, 95% CI 1.71-1.83, p < 0.001), with a similar pattern across age strata. These associations were consistent across the 12 individual health centres. From the cross-sectional surveys, females were more likely than males to report fever in the past 2 weeks and seek care at the local health centre (7.5% vs. 4.7%, p = 0.001) with these associations significant for those 15-39 years (RR = 2.49, 95% CI 1.17-5.31, p = 0.018) and over 39 years (RR = 2.56, 95% CI 1.00-6.54, p = 0.049). CONCLUSIONS: Females disproportionately contribute to the burden of malaria diagnosed at public health facilities in Uganda, especially once they reach childbearing age. Contributing factors included more frequent visits to these facilities independent of malaria and a higher reported risk of seeking care at these facilities for febrile illnesses

Dataset for the article: Mapping malaria incidence using routine health facility surveillance data in Uganda

Data availability statement: Data are available in a public, open access repository. The datasets generated and/or analysed during the current study, in addition to sample code for model fitting, are available in the github repository, https://github.com/aeepstein/uganda_risk_map

Mapping malaria incidence using routine health facility surveillance data in Uganda

Introduction Maps of malaria risk are important tools for allocating resources and tracking progress. Most maps rely on cross-sectional surveys of parasite prevalence, but health facilities represent an underused and powerful data source. We aimed to model and map malaria incidence using health facility data in Uganda.Methods Using 24 months (2019–2020) of individual-level outpatient data collected from 74 surveillance health facilities located in 41 districts across Uganda (n=445 648 laboratory-confirmed cases), we estimated monthly malaria incidence for parishes within facility catchment areas (n=310) by estimating care-seeking population denominators. We fit spatio-temporal models to the incidence estimates to predict incidence rates for the rest of Uganda, informed by environmental, sociodemographic and intervention variables. We mapped estimated malaria incidence and its uncertainty at the parish level and compared estimates to other metrics of malaria. To quantify the impact that indoor residual spraying (IRS) may have had, we modelled counterfactual scenarios of malaria incidence in the absence of IRS.Results Over 4567 parish-months, malaria incidence averaged 705 cases per 1000 person-years. Maps indicated high burden in the north and northeast of Uganda, with lower incidence in the districts receiving IRS. District-level estimates of cases correlated with cases reported by the Ministry of Health (Spearman’s r=0.68, p&lt;0.0001), but were considerably higher (40 166 418 cases estimated compared with 27 707 794 cases reported), indicating the potential for underreporting by the routine surveillance system. Modelling of counterfactual scenarios suggest that approximately 6.2 million cases were averted due to IRS across the study period in the 14 districts receiving IRS (estimated population 8 381 223).Conclusion Outpatient information routinely collected by health systems can be a valuable source of data for mapping malaria burden. National Malaria Control Programmes may consider investing in robust surveillance systems within public health facilities as a low-cost, high benefit tool to identify vulnerable regions and track the impact of interventions