Dataset Information

Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System.

ABSTRACT: BACKGROUND:Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide. OBJECTIVE:This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French Guiana and Brazil. METHODS:Data reconciliation rules based on expert knowledge were defined and applied to the heterogeneous data provided by the existing malaria surveillance systems of both countries. Visualization dashboards were designed to facilitate progressive data exploration, analysis, and interpretation. Dedicated advanced open source and robust software solutions were chosen to facilitate solution sharing and reuse. RESULTS:A database gathering the harmonized data on cross-border malaria epidemiology is updated monthly with new individual malaria cases from both countries. Online dashboards permit a progressive and user-friendly visualization of raw data and epidemiological indicators, in the form of time series, maps, and data quality indexes. The monitoring system was shown to be able to identify changes in time series that are related to control actions, as well as differentiated changes according to space and to population subgroups. CONCLUSIONS:This cross-border monitoring tool could help produce new scientific evidence on cross-border malaria dynamics, implementing cross-border cooperation for malaria control and elimination, and can be quickly adapted to other cross-border contexts.

SUBMITTER: Saldanha R

PROVIDER: S-EPMC7492983 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System.

Saldanha Raphael R Mosnier Émilie É Barcellos Christovam C Carbunar Aurel A Charron Christophe C Desconnets Jean-Christophe JC Guarmit Basma B Gomes Margarete Do Socorro Mendonça MDSM Mandon Théophile T Mendes Anapaula Martins AM Peiter Paulo César PC Musset Lise L Sanna Alice A Van Gastel Benoît B Roux Emmanuel E

JMIR public health and surveillance 20200901 3

<h4>Background</h4>Cross-border malaria is a significant obstacle to achieving malaria control and elimination worldwide.<h4>Objective</h4>This study aimed to build a cross-border surveillance system that can make comparable and qualified data available to all parties involved in malaria control between French Guiana and Brazil.<h4>Methods</h4>Data reconciliation rules based on expert knowledge were defined and applied to the heterogeneous data provided by the existing malaria surveillance syste ...[more]

PMID: 32663141

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Project description:BackgroundThe Mekong Basin Disease Surveillance cooperation (MBDS) is one of several sub-regional disease surveillance networks that have emerged in recent years as an approach to transnational cooperation for infectious disease prevention and control. Since 2003 MBDS has pioneered a unique model for local cross-border cooperation. This study examines stakeholders' perspectives of these MBDS experiences, based on a survey of local managers and semi-structured interviews with MBDS leaders and the central coordinator.ResultsFifteen managers from 12 of 20 paired cross-border sites completed a written survey. They all monitor most or all of the 17 diseases agreed upon for MBDS surveillance information sharing. Fourteen agreed or strongly agreed with statements about the core MBDS values of cooperation, mutual trust, and transparency, and their own contributions to national and regional disease control (average score of 4.4 of 5.0). Respondents felt they implemented well to very well activities related to surveillance reporting (average scores 3.4 to 3.9 of 4.0), using computers for their work (3.9/4.0), and using surveillance data for action (3.8/4.0). Respondents reported that they did worst in implementing research (2.1/4.0) and somewhat poorly for local laboratory testing (2.9/4.0) and local coordination with cross-border counterparts (2.9/4.0), although all 15 maintain a list with contact information for these counterparts and many know their counterparts. Implementation of specified activities within their collective regional action plan was uneven across the cross-border sites. Most respondents reported positive lessons learned about local cooperation, information sharing and joint problem solving, based on trusting relationships with their cross-border counterparts. They recommend expansion of cross-border sites within MBDS and consideration of the cross-border cooperation model by other sub-regional networks.ConclusionsMBDS has over a decade of experience with its model of local cross-border cooperation in disease surveillance and control. Frontline managers have documented success with this model, strongly support it and recommend its expansion within and beyond the MBDS network. The MBDS cross-border cooperation model is standing the test of time as a solid approach to building and sustaining the public health capabilities needed for disease surveillance and control from the local to national and global levels.

Project description:BackgroundIdentifying human and malaria parasite movements is important for control planning across all transmission intensities. Imported infections can reintroduce infections into areas previously free of infection, maintain 'hotspots' of transmission and import drug resistant strains, challenging national control programmes at a variety of temporal and spatial scales. Recent analyses based on mobile phone usage data have provided valuable insights into population and likely parasite movements within countries, but these data are restricted to sub-national analyses, leaving important cross-border movements neglected.MethodsNational census data were used to analyse and model cross-border migration and movement, using East Africa as an example. 'Hotspots' of origin-specific immigrants from neighbouring countries were identified for Kenya, Tanzania and Uganda. Populations of origin-specific migrants were compared to distance from origin country borders and population size at destination, and regression models were developed to quantify and compare differences in migration patterns. Migration data were then combined with existing spatially-referenced malaria data to compare the relative propensity for cross-border malaria movement in the region.ResultsThe spatial patterns and processes for immigration were different between each origin and destination country pair. Hotspots of immigration, for example, were concentrated close to origin country borders for most immigrants to Tanzania, but for Kenya, a similar pattern was only seen for Tanzanian and Ugandan immigrants. Regression model fits also differed between specific migrant groups, with some migration patterns more dependent on population size at destination and distance travelled than others. With these differences between immigration patterns and processes, and heterogeneous transmission risk in East Africa and the surrounding region, propensities to import malaria infections also likely show substantial variations.ConclusionThis was a first attempt to quantify and model cross-border movements relevant to malaria transmission and control. With national census available worldwide, this approach can be translated to construct a cross-border human and malaria movement evidence base for other malaria endemic countries. The outcomes of this study will feed into wider efforts to quantify and model human and malaria movements in endemic regions to facilitate improved intervention planning, resource allocation and collaborative policy decisions.

Dataset Information

Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System.

Publications

Contributing to Elimination of Cross-Border Malaria Through a Standardized Solution for Case Surveillance, Data Sharing, and Data Interpretation: Development of a Cross-Border Monitoring System.

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