Mapping malaria incidence using routine health facility surveillance data in Uganda

被引:5
|
作者
Epstein, Adrienne [1 ]
Namuganga, Jane Frances [2 ]
Nabende, Isaiah [2 ]
Kamya, Emmanuel Victor [2 ]
Kamya, Moses R. [2 ,3 ]
Dorsey, Grant [4 ]
Sturrock, Hugh [4 ,5 ]
Bhatt, Samir [6 ,7 ]
Rodriguez-Barraquer, Isabel [4 ]
Greenhouse, Bryan [4 ]
机构
[1] Univ Liverpool Liverpool Sch Trop Med, Dept Vector Biol, Liverpool, England
[2] Infect Dis Res Collaborat, Kampala, Uganda
[3] Makerere Univ, Dept Med, Kampala, Uganda
[4] Univ Calif San Francisco, Dept Med, San Francisco, CA USA
[5] Univ Calif San Francisco, Malaria Eliminat Initiat, San Francisco, CA USA
[6] Univ Copenhagen, Dept Publ Hlth, Copenhagen, Denmark
[7] Imperial Coll London, Dept Infect Dis Epidemiol, London, England
来源
BMJ GLOBAL HEALTH | 2023年 / 8卷 / 05期
关键词
malaria; geographic information systems; epidemiology; PLASMODIUM-FALCIPARUM; TIME;
D O I
10.1136/bmjgh-2022-011137
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
IntroductionMaps 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.MethodsUsing 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.ResultsOver 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<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).ConclusionOutpatient 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.
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页数:10
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