Development of a data collection and management system in West Africa: challenges and sustainability

Abstract

BackgroundDeveloping and sustaining a data collection and management system (DCMS) is difficult in malaria-endemic countries because of limitations in internet bandwidth, computer resources and numbers of trained personnel. The premise of this paper is that development of a DCMS in West Africa was a critically important outcome of the West African International Centers of Excellence for Malaria Research. The purposes of this paper are to make that information available to other investigators and to encourage the linkage of DCMSs to international research and Ministry of Health data systems and repositories.MethodsWe designed and implemented a DCMS to link study sites in Mali, Senegal and The Gambia. This system was based on case report forms for epidemiologic, entomologic, clinical and laboratory aspects of plasmodial infection and malarial disease for a longitudinal cohort study and included on-site training for Principal Investigators and Data Managers. Based on this experience, we propose guidelines for the design and sustainability of DCMSs in environments with limited resources and personnel.ResultsFrom 2012 to 2017, we performed biannual thick smear surveys for plasmodial infection, mosquito collections for anopheline biting rates and sporozoite rates and year-round passive case detection for malarial disease in four longitudinal cohorts with 7708 individuals and 918 households in Senegal, The Gambia and Mali. Major challenges included the development of uniform definitions and reporting, assessment of data entry error rates, unstable and limited internet access and software and technology maintenance. Strengths included entomologic collections linked to longitudinal cohort studies, on-site data centres and a cloud-based data repository.ConclusionsAt a time when research on diseases of poverty in low and middle-income countries is a global priority, the resources available to ensure accurate data collection and the electronic availability of those data remain severely limited. Based on our experience, we suggest the development of a regional DCMS. This approach is more economical than separate data centres and has the potential to improve data quality by encouraging shared case definitions, data validation strategies and analytic approaches including the molecular analysis of treatment successes and failures.Electronic supplementary materialThe online version of this article (10.1186/s40249-018-0494-4) contains supplementary material, which is available to authorized users.

Clustering of asymptomatic Plasmodium falciparum infection and the effectiveness of targeted malaria control measures

“…This study examined four communities in Mali, Senegal and The Gambia. The study sites in Mali were the villages of Dangassa and Dioro: Dangassa is a rural community in southwest Mali on the Niger River 100 km southwest of Bamako and 160 km north of the Guinea border with year-round malaria transmission [20]. In contrast, Dioro is a rural community in the Segou Region of Mali on the Niger River at the southern edge of the Sahel which is 290 km northeast of Bamako and has primarily seasonal transmission (October-December in the rainy season) [21].…”

“…Transmission seasons varied across study sites and were classified as "dry" or "rainy" [20][21][22][23]. For the Mali sites, seasons were classified as dry (January 1-June 30) and rainy (July 1-December 31) [20,21]; for The Gambia as dry (October 1-June 15) [22] and rainy (June 16-September 30) and for Senegal as dry (December 1-April 30) and rainy (May 1-November 30) [23].…”

Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

“…The transmission dynamic is bimodal, with the start and end of the rainy season (in June–August and December–January) accounting for peak transmission. Measures such as Long Lasting Insecticidal Nets (LLINs), Artemisinin-based Combination Therapies (ACTs), and Intermittent Preventive Treatment during pregnancy (IPTp) have been in effect in Dangassa since 2008 [ 3 , 23 ].…”

“…From 2012 to 2017, an observational study assessed the impact of malaria control measures at four study sites, including Dangassa [ 23 ]. An open dynamic cohort of 1400 participants of all ages (0–85 years) and sex were recruited.…”

“…This technique has been used recently in many modeling applications, such as influenza incidence rate modeling with climate covariates [ 22 ], but has yet to be used in the context of malaria. In this study, we use such methods to identify the underlying factors that shape the patterns of malaria prevalence in Dangassa, a rural Malian village which experiences bimodal malaria transmission dynamics [ 3 , 23 ]. Proper understanding of both past and future influences of environment and meteorological factors on malaria risk will help identify the relevant variables that contribute to the spread of the disease and to prevent outbreaks based on past malaria incidence rate and recognizable environmental climatic patterns.…”