Strengthening surveillance systems for malaria elimination: a global landscaping of system performance, 2015-2017

Abstract

Background: Surveillance is a core component of an effective system to support malaria elimination. Poor surveillance data will prevent countries from monitoring progress towards elimination and targeting interventions to the last remaining at-risk places. An evaluation of the performance of surveillance systems in 16 countries was conducted to identify key gaps which could be addressed to build effective systems for malaria elimination.

Methods: A standardized surveillance system landscaping was conducted between 2015 and 2017 in collaboration with governmental malaria programmes. Malaria surveillance guidelines from the World Health Organization and other technical bodies were used to identify the characteristics of an optimal surveillance system, against which systems of study countries were compared. Data collection was conducted through review of existing material and datasets, and interviews with key stakeholders, and the outcomes were summarized descriptively. Additionally, the cumulative fraction of incident infections reported through surveillance systems was estimated using surveillance data, government records, survey data, and other scientific sources.

Results: The landscaping identified common gaps across countries related to the lack of surveillance coverage in remote communities or in the private sector, the lack of adequate health information architecture to capture high quality case-based data, poor integration of data from other sources such as intervention information, poor visualization of generated information, and its lack of availability for making programmatic decisions. The median percentage of symptomatic cases captured by the surveillance systems in the 16 countries was estimated to be 37%, mostly driven by the lack of treatment-seeking in the public health sector (64%) or, in countries with large private sectors, the lack of integration of this sector within the surveillance system.

Conclusions: The landscaping analysis undertaken provides a clear framework through which to identify multiple gaps in current malaria surveillance systems. While perfect systems are not required to eliminate malaria, closing the gaps identified will allow countries to deploy resources more efficiently, track progress, and accelerate towards malaria elimination. Since the landscaping undertaken here, several countries have addressed some of the identified gaps by improving coverage of surveillance, integrating case data with other information, and strengthening visualization and use of data.

Keywords: Elimination; Malaria; Surveillance; Surveillance system.

Fig. 1

Surveillance loop framework with key indicators for the primary components of data collection, reporting, analysis, and response

Fig. 2

Distribution of values from country assessments for seeking care, receiving diagnosis, facility inclusion, and reporting rates, along with the country-specific total coverage resulting from their product in a the GMS (n = 4 countries), b Mesoamerica and Hispaniola (n = 6 countries), c Southern Africa (n = 6 countries), and d Globally (n = 16 countries). The box and whisker plots include the median values, minimum and maximum ranges, as well as upper and lower quartiles in the box. In the x axis, percentage values of those seeking care are of incident symptomatic malaria infections, the percentage receiving correct diagnosis is the fraction of those seeking care, the percentage of cases from facilities included in the surveillance system is the fraction of those receiving the correct diagnosis, and the percentage of cases reported is the fraction of the cases from facilities included in the surveillance system. The total proportion represents the multiplication of the percentages at each step of the cascade