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

Abstract

Background: Developing 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.

Methods: We 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.

Results: From 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.

Conclusions: At 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.

Keywords: Data (database) management system; Data collection; Diseases of poverty; Malaria; Plasmodium falciparum.

Fig. 1

Organization of the Longitudinal Cohort Study. With four study sites in three countries, this longitudinal study examined the prevalence of P. falciparum infection by Active Case Detection (biannual thick smears, ACD) and the incidence of disease by Passive Case Detection (PCD). Information from household surveys and data from ACD and PCD were recorded on Case Report Forms (CRFs) and entered in a computerized database using the StudyTRAX software. GIS: Geographic information system; ICEMR: International Center of Excellence for Malaria Research; LLIN: Long-lasting insecticidal net; RDT: Rapid diagnostic test

Fig. 2

Seasonal changes in the prevalence of Plasmodium falciparum infection (based on the frequency of positive thick blood smears). The prevalence of P. falciparum infection was high both before and at the end of the season in Dangassa (> 40%). However, it was low (< 2%) before and at the end of malaria season in Madina Fall. Only Gambissara demonstrated the expected pattern, modest low levels of infection (5%) before the malaria season and a substantial increase to 16% at the end of the season. In contrast, the prevalence of infection in Dioro actually decreased between the beginning and end of the malaria season (from 25 to 8%). Pre-season prevalence bars are in red; end of season prevalence bars are in green

Fig. 3

Annual incidence of uncomplicated malaria in a longitudinal cohort. The annual incidence of uncomplicated P. falciparum malaria was highest in Dangassa, 10-fold lower in both Dioro and Gambissara and 100-fold lower in Madina Fall. Bars for the incidence of uncomplicated malaria are light gray for 2013 and dark gray for 2014

Fig. 4

Developing a data collection and management system in West Africa. Development of a regional data collection and management system (DCMS) was based on support from Ministries of Health in the participating countries, WHO, USAID, the President’s Malaria Initiative, the National Institutes of Health and the Centers for Disease Control. Institutional support was provided by the University of Bamako, the University Cheikh Anta Diop in Dakar and the Medical Research Council in Gambia. Computing and epidemiologic expertise were provided by the participating institutions. As a result of the ICEMR workshops, investigators and their DCMS colleagues developed greater expertise in study design, data management and validation, management of electronic files and the development of applications to search the ICEMR database. ICEMR: International Center of Excellence for Malaria Research; IRB: Institutional Review Board; WHO: World Health Organization

Fig. 5

Sustaining a data collection and management system in West Africa. The data collection and management system (DCMS) in West Africa has increased opportunities for training with international (Fogarty, PEER) and host country support, publication (this is the first ICEMR paper on data collection and development of the DCMS) and the ability (opportunity) for West African investigators to access international resources such as Medline and genome-related databases on a regular basis. GIS: Geographic information system; NGO: Non-governmental organisation; NCBI: National Center for Biotechnology Information; BLAST: Basic local alignment search tool; PLoS NTD: PLoS Neglected Tropical Diseases