Developing a digital platform for sub-district level malaria burden stratification mapping using routine health facility case data – guiding the national transition to targeted malaria control, version 1.0
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Date
2022-07-26
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Kamuzu University of Health Sciences
Abstract
Study type: Secondary data analysis
Research problem: With the continued reduction of malaria prevalence at the national level
after many years of intensive malaria interventions, community-level transmission becomes
more important. Focusing on the trends in malaria transmission at the national level may
mask the heterogeneities that exist at the sub-district level. Therefore, it is important to
understand the disease dynamics at the community level to inform strategies that can
eventually lead to the elimination of the disease.
Main objective: The main objective is to use routinely reported health facility-level malaria
case data to produce sub-district level estimates of clinical malaria incidence in Malawi and
stratify the country by different levels of incidence for more targeted malaria intervention.
Specific objectives:
• Develop standardised procedures for data collation and data management of routinely
reported data
• Undertake a spatial analysis to stratify the country into the predefined risk categories at
regular intervals, using available data on current intervention coverage,
climate/environment, and evidence of insecticide resistance.
• Develop a digital dashboard which can be accessed by the National Malaria Control
Programme (NMCP) and district programme coordinators to display interactive maps,
summaries of the resulting analysis and generate automated reports
• Train staff at the NMCP and the Central Monitoring and Evaluation Division (CMED) to
update the data and maintenance analyses on a regular basis with the support of the
Ministry of Health’s Digital Heath Division (DHD).
• Support relevant technical working groups (TWGs) to use the maps when planning
upcoming interventions.
Methodology: We will obtain monthly aggregated malaria case data from the Health
Management Information System (HMIS) known as DHIS21 at the health facility level. After
data processing, we will apply geospatial statistical methods to estimate malaria incidence
over time, incorporating the effects of climate, environment, and malaria intervention
activities. Our results will then be visualised within a digital dashboard which will be
integrated within NMCP surveillance systems at the national and district levels. Expected results and their dissemination
We anticipate that our analysis will reveal the spatial and temporal heterogeneities in
malaria transmission across the country. Results will be shared with COMREC and the
Ministry of Health at relevant technical working group meetings and the joint KUHeS and
MLW research dissemination conference. We will also publish the results in peer-reviewed
journals.
Description
Study type: Secondary data analysis