Enhancing Decision Support for Vector-Borne Disease Control Programs—The Disease Data Management System

Data is at the core of any successful vector-borne disease control or elimination activity. At the early stages of control, monitoring data can help prioritize limited funding and resources to maximize impact. During the pre-elimination and elimination phases, surveillance data itself becomes the primary intervention by quickly identifying persistent transmission [1]. In addition, it has been identified that spatial decision-support tools will be crucial to integrate with health information systems (HIS) as countries strive for elimination [2]. The Disease Data Management System (DDMS) is a tool designed to meet the data management and decision-support needs of vector-borne disease control programs as they transition through control to elimination. The development and functionality of the DDMS has been described elsewhere [3], and particular advantages and disadvantages are highlighted in Box 1. Here, we describe the implementation and impact of the system in disease-endemic countries, user feedback, and future challenges. Box 1. Advantages and Disadvantages of the DDMSAdvantages High configurability means that the system can be adjusted for any vector-borne disease control program. Capable of supporting decision making from control through elimination phases. Decision support, reporting, and spatial visualization components for multiple diseases integrated into a single tool. Query builders mean that the user is not limited to pre-defined reports but can easily create custom queries on demand. Disadvantages High configurability means that well-trained administrators are required. System versatility sometimes causes untrained users to experience the DDMS as being overly complex. Direct mobile data capture not currently integrated. System Implementation The DDMS has been implemented in seven countries in Africa and Asia (Table 1). All countries have employed a similar system architecture in which the database is accessible via the internet and there is bidirectional flow of data and outputs at all organizational levels (Fig 1). Table 1 Description of where the DDMS is currently being implemented, for what purpose, and by what organization. Fig 1 A typical setup for the implementation of the DDMS. Overall, the primary impact in most countries has been increased accessibility of data and therefore more informed decision making. This is most apparent in Zambia, where the Insecticide Resistance Management Technical Working Group uses DDMS outputs, in the form of maps and reports, to inform decisions related to management of insecticide resistance [4]. The implementation in Zambia, although a good example of how the DDMS can impact decision making, has not been without its challenges. Since November 2014, the DDMS has not been used, primarily because of a loss of momentum as the responsibility of maintaining the system shifted between malaria control partners. This has highlighted the need to bolster the capacity of related systems (organizational data culture, data collection procedures, IT infrastructure) to support DDMS implementations. The prospect of increased data accessibility prompted the Africa IRS (AIRS) project, funded by the President’s Malaria Initiative, to adopt the DDMS after initial trials in Zambia and Ethiopia [5]. This will involve the deployment of the DDMS as the entomological database in eight AIRS countries in sub-Saharan Africa. The DDMS in each country can be accessed by stakeholders nationally and internationally, which has made comparison of data at the international level more feasible.