Using malaria data to help reach the hard-to-reach: Perspectives from Kenya
Good policy decisions rely on the availability and use of good data. Dr. Victor Alegana, a research fellow at the Kenya Medical Research Institute, puts it quite simply: “It is dangerous to not use data for decision-making. It is like driving a car without mirrors, as you will be moving in the dark.”
But using data to formulate policy is not always straightforward. Policy makers must identify what data should be collected, the best way to share it, and the best way to use it to allocate resources. It is clear we need to focus on the connection between research, policy, and health outcomes to target the hard-to-reach populations who are currently missing out.
For example, efforts to control malaria have saved millions of lives in the past decade alone, but eradication remains a challenge. The new strategy of the U.S. government’s Presidents Malaria Initiative (PMI) includes making better use of malaria incidence data to target populations for whom access to malaria prevention and treatment remains a life-and-death challenge.
Experts from Kenya share their experience using data to inform malaria programming decisions
- Dr. Victor Alegana, a research fellow at the Kenya Medical Research Institute (KEMRI), a state-funded research facility
- Lilian Dayo, the county malaria control coordinator for Kisumu County
- Dr. Onyango Oluoch, the county malaria control coordinator in Busia County
- Dr. Elvis Oyugi, technical lead for Surveillance, Monitoring & Evaluation and Operations Research of the Kenyan Ministry of Health’s Division of the National Malaria Programme.
Under programs such as The Demographic and Health Surveys (DHS) Program, which collects health and population data, and PMI Measure Malaria, which strengthens capacity to collect, analyze, and use routine malaria health data, ICF has worked with these and other Kenyan experts dedicated to using data to reduce the burden of disease.
The following article is a summary of our discussion.
Timing is everything
According to Dr. Alegana, the latest KMIS findings were very timely. He used the survey’s malaria prevalence data to update the national malaria program’s malaria risk stratification map. Previously, researchers had relied on a 2010 data map and the new data helped inform updates to programming and budgets for the 2019 – 2023 National Malaria Strategy. Dr. Alegana recognized that the KMIS captured the effects of the COVID-19 pandemic on malaria control efforts. For example, it showed the national percentage of households owning at least one insecticide-treated net (ITN) dropped from 63% in 2015 to 49% in 2020 due to delays in distribution.
Households with at least one insecticide-treated mosquito net (ITN)
Data from the DHS Program’s StatCompiler demonstrate the drop in ITN usage in 2020
Dr. Alegana also noted that the KMIS provided a fair summary of current case management and treatment practices. “This will help the program provide better policies going forward,” he said. Lilian Dayo echoed these sentiments and said county-level data on parasite prevalence and ITN use was helpful in adjusting Kisumu County interventions.
Data presentation and sharing is essential
Lilian Dayo also pointed out that media and national policymaker involvement are both essential to achieve positive results. The new data from the KMIS were shared during a conference marking World Malaria Day on April 25th, 2021. This created awareness that was in turn used to generate broader interest and use of the new information.
Dr. Oluoch also noted that local decision-makers are using the KMIS data more than ever and that dissemination and use of malaria data in Busia County has improved: “The future of malaria data use is bright,” he says. “90% of program officers can now analyze, navigate, and interact with data compared to 10%, five years ago.”
Invest in what is working…
Data can show the effectiveness of specific interventions. For example, Dr. Oluoch was pleased that ITN use for children in Busia had increased from 67% to 79% and ITN use among pregnant women had increased from 59% to 80.5%, based on county-level modeling using MIS data.
….and address what is not working
In contrast, Dr. Olouch's analysis showed that the health-seeking behavior for children under five years in Busia County and especially in government-run health facilities had decreased from 73.6% in 2015 to 60.1% in 2020. Ms. Dayo also noted that in Kisumu County, the proportion of women receiving at least three doses of intermittent preventive treatment in pregnancy (IPTp) dropped from around 50% to around 25% in the last five years also based on county-level modeling using MIS data. Dr. Oluoch is now considering new strategies, such as talking to county leadership to review policies, and engaging with community health volunteers to raise awareness and facilitate referrals to health care facilities.
Reaching the hard-to-reach—challenges and opportunities
According to our interviewees, the challenge now is getting more detailed local data to identify and target hard-to-reach populations.
Dr. Oluoch said he would like to see findings published on malaria prevalence at the lowest sub-county and ward level to help sub-county officials, who have the means to address findings specific to their jurisdiction. Dr. Oyugi expressed similar sentiments. He would like to see routine reporting of county-specific severe malaria in the endemic coastal regions, as well as the introduction of IPTp targets at local level. “There is energy being invested towards data-improved decisions in the country and dissemination should reach the lowest levels to impact behavior change,” he said.
Dr. Oluoch confirmed that micro-stratified data could allow for replication of interventions that have worked well elsewhere in counties with similar levels of malaria prevalence such as Busia and Siaya. He suggested, for example, that successful interventions in Migori County could be replicated in Busia.
The road forward
Dr. Oluoch predicts that the demand for data will continue to grow as stakeholders push for information to make better decisions. He hopes to see more digitization of health records to improve access and use of malaria services at the facility and community level. Dr Oyugi concurred. “The future of effective malaria strategy lies in making data available widely through the latest technology and infrastructure,” he said.
Kenya’s national government is currently developing a malaria dashboard through the Kenya Health Information System (that is the KHIS using the DHIS2 open-source health management information platform) to analyze inpatient, outpatient, comorbidity, and intervention data. Government officials are also working on a malaria data repository that will bring together routine surveillance data from health facilities, as well as data from the broader research community, in real-time under one interface to enhance informed decision-making at all levels.
To help the hard-to-reach populations, our panel of experts recommended introducing more cost-effective methods, such as combining traditional data collection and dissemination methods with less expensive new ones such as mobile data, cluster, and health facility data.
Sharpening the focus on the hard-to-reach
Our panel of interviewees concluded that quality data is a vital tool in helping Kenya implement its 2019 – 2023 National Malaria Strategy. While data literacy and use are improving overall policy initiatives across the country, they said that maintaining a focus on lower levels is crucial in the drive to help hard-to-reach populations.
