ArticleThe American journal of tropical medicine and hygiene2020
A Robust Estimator of Malaria Incidence from Routine Health Facility Data.
Article in The American journal of tropical medicine and hygiene, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Impact of seasonal malaria chemoprevention: a plausibility evaluation of routine data from health facilities in three implementing states in Nigeria.Malaria journal · 2025Article
- Seasonal malaria chemoprevention in northern Mozambique: a cost-effectiveness analysis.Malaria journal · 2025Article
- Impact of Control Interventions on Malaria Incidence in the General Population of Mali.Journal of epidemiology and global health · 2025Article
- Prevalence and factors associated with malaria among children aged 6 months to 10 years in the Greater Accra Region of Ghana: a community-based cross-sectional survey.Malaria journal · 2024Article
- Malaria surveillance reveals parasite relatedness, signatures of selection, and correlates of transmission across Senegal.Nature communications · 2023Article
- Assessing the utility of pregnant women as a sentinel surveillance population for malaria in Geita, Tanzania, 2019 - 2021.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2023Article
- Mapping malaria incidence using routine health facility surveillance data in Uganda.BMJ global health · 2023Article
- Spatio-Temporal Bayesian Models for Malaria Risk Using Survey and Health Facility Routine Data in Rwanda.International journal of environmental research and public health · 2023Article
- Notification of malaria cases in the Brazilian Amazon Basin from 2010 to 2020: an analysis of the reporting times.Malaria journal · 2023Article
- Stratification at the health district level for targeting malaria control interventions in Mali.Scientific reports · 2022Article
- The epidemiology and detectability of asymptomatic plasmodium vivax and plasmodium falciparum infections in low, moderate and high transmission settings in Ethiopia.Malaria journal · 2021Article
- Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data.Malaria journal · 2020Article
- Estimating Malaria Incidence through Modeling Is a Good Academic Exercise, but How Practical Is It in High-Burden Settings?The American journal of tropical medicine and hygiene · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Routine incident malaria case data have become a pillar of malaria surveillance in sub-Saharan Africa. These data provide granular, timely information to track malaria burden. However, incidence data are sensitive to changes in care seeking rates, rates of testing of suspect cases, and reporting completeness. Based on a set of assumptions, we derived a simple algebraic formula to convert crude incidence rates to a corrected estimation of incidence, adjusting for biases in variable and suboptimal rates of care seeking, testing of suspect cases, and reporting completeness. We applied the correction to routine incidence data from Guinea and Mozambique, and aggregate data for sub-Saharan African countries from the World Malaria Report. We calculated continent-wide needs for malaria tests and treatments, assuming universal testing but current care seeking rates. Countries in southern and eastern Africa reporting recent increases in malaria incidence generally had lower overall corrected incidence than countries in Central and West Africa. Under current care seeking rates, the unmet need for malaria tests was estimated to be 160 million (M) (interquartile range [IQR]: 139-188) and for malaria treatments to be 37 M (IQR: 29-51). Maps of corrected incidence were more consistent with maps of community survey prevalence than was crude incidence in Guinea and Mozambique. Crude malaria incidence rates need to be interpreted in the context of suboptimal testing and care seeking rates, which vary over space and time. Adjusting for these factors can provide insight into the spatiotemporal trends of malaria burden.
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