INESS Key activities
Health and Demographic Surveillance Systems (HDSSs) provide a useful framework for tracking demographic and health dynamics in defined geographical areas over time. HDSS captures information on residence, updates vital events and covers the whole or part of a district where all individuals, their relationships, ages as well as other attributes, are recorded longitudinally along with events affecting population dynamics including birth, death and migrations (in and out). Most importantly, HDSS sites monitor cause of death as a major indicator of population health. Together with data on residence and demographic events the HDSS captures several other types of socio-economic data including household wealth and education status as additional important information for population health profiles. At the same time the HDSS co-exists with a facility-based data source in a form of Health Management Information System (HMIS) which captures health services attendance, diagnosis, service and treatment data as individuals come into contact with the formal health system for either preventive or curative services from one of the health facilities serving the Demographic Surveillance Area (DSA).
Integrating the two data sources would provide both the numerator and the denominator population for computation of both disease incidence rates in the population and health service coverage rates in the health system, essential data health system analysis, health planning and policy formulation which is currently lacking. These linkages would as well improve management and health service provision and policies in rural settings where data collection on vital information is weak. For instance, linking the two databases will enhance active follow up of treatment cohorts and tracing patients on specific treatment regimes to their location if need be (e.g. people on ACTs, IPTp; IPTi; TB DOTS, Ante and post-natal care) in order to understand system performance.
The Data linkage task team aims to provide a means to link information generated from the two data systems in the INDEPTH Effectiveness Studies Platform is essential to the success of the Platform. It will develop, adapt and implement a practical mechanism to appropriately link the HDSS with facility-based data from HMIS in a way that is appropriate to individual HDSS and Health System settings for the respective countries. This would be achieved by providing a unique identification tag for the records of individuals when they visit the facility. In order to make sure the privacy of both HDSS members and patients is safeguarded the system will ensure that the health providers cannot become aware of information the DSS holds about the individual while at the same time HDSS staff and analysts cannot access individual patient and medical records of the health system. The data linkage will be designed to allow analysis of anonymised data while still retaining population attributes from the DSS database.
Cost and Policy analysis
The INESS studies seek to inform policy makers by providing the rationale for choices in the adoption of effective drugs. Estimating costs and cost-effectiveness of the studies is crucial as the studies are rolled out to enable policy makers make a sound choice among the various alternatives presented as first line drugs or as drugs for special groups of the population. There are two main goals of costing the introduction of a new antimalarial for the INESS Studies. The first is to provide evidence on whether the new antimalarial is of high, moderate, or low cost-effectiveness compared to the existing first line drugs in use in participating countries. The second is to provide health planners and donors with information on the cash expenditures (the financial costs) that would be needed to introduce a new policy for the new antimalarials in the first place and then to keep it running. The first type of information would assist decision-makers in countries as well as other African countries that are considering using the new antimalarials and the financial analysis would be useful for monitoring, planning and budgeting purposes.
Further, policy change usually involves changing the drug policy guidelines, developing treatment guidelines, developing a training manual for health workers and implements, developing IEC materials, distribution guidelines, sensitization at the various levels, advocacy and lobbying with key stakeholders which requires documentation of the entire process and costing the process to help inform policy makers. Also the new drugs have to be procured and cost of the drugs, the procurement process and the distribution and regulation regarding the drug needs to be documented and the cost ascertained. Service delivery factors such as training health workers, private providers, supervision, and sensitization at the community level are all factors that will influence a country to want to change its drug policy.
Thus in order to capture and cost the process of policy change we will first review and collect data to document the process of policy change for antimalarial drug policy in each country.
Different levels of policy change will be identified and the process documented. Different levels of policy change such as the national, regional/provincial and the district levels are envisaged for the stakeholder interviews.
Data on the global drug subsidy in countries will be collated to document the process and the cost of this subsidy. District level contextual factors such as floods, drought, policy change at the district level that are likely to have an impact on the outcomes of the INESS studies should be observed, documented and the costs obtained in each district and site.
Community and Provider Acceptability
The qualitative research component for the INDEPTH Safety and Effectiveness Studies Platform is designed to provide insight into the contextual factors that affect people’s willingness and ability to seek care and provide appropriate treatment. To that end, the qualitative data collection activities for this project are conceptually integrated into the household and health facilities studies that are described in Modules 1 (Access), 3 (Provider Compliance), and 4 (Patient Adherence). To examine the social, cultural, and behavioral factors that facilitate or impede the uptake and adherence to new antimalarial combination therapies as they are introduced into real-life settings.
Other measures of effects and contextual determinants of malaria
The main output of this module is to document and interpret the trends of mortality and morbidity taking into consideration all the factors. Controlling for confounders and effect modifiers will require documentation in trends of coverage of malaria preventive interventions such as ITNs, IRS coverage, and IPT. Other contextual determinants, including health system changes, which may act as confounders and/or effect modifiers will also be documented to the extent data is available. Depending on the intensity of transmission, widespread use of ACTs may reduce gametocyte rates and hence malaria transmission indices. Entomologic inoculation rates will be monitored in HDSS sites with entomology capacity. INESS will be able to determine the public health impact of treatment failure identified through data linkage and cohorts through several markers such as malaria associated morbidity as reported in health facilities and in household surveys.