Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study
Abstract Background Reactive case detection could be a powerful tool in malaria elimination, as it selectively targets transmission pockets. However, field operations have yet to demonstrate under which conditions, if any, reactive case detection is best poised to push a region to elimination. This...
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doaj-302421ed167c41e4b14b16ef0c9f3b392020-11-25T00:34:38ZengBMCMalaria Journal1475-28752017-06-0116111710.1186/s12936-017-1903-zEffectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling studyJaline Gerardin0Caitlin A. Bever1Daniel Bridenbecker2Busiku Hamainza3Kafula Silumbe4John M. Miller5Thomas P. Eisele6Philip A. Eckhoff7Edward A. Wenger8Institute for Disease ModelingInstitute for Disease ModelingInstitute for Disease ModelingNational Malaria Elimination Centre, Ministry of HealthPATH Malaria Control and Elimination Partnership in AfricaPATH Malaria Control and Elimination Partnership in AfricaCenter for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical MedicineInstitute for Disease ModelingInstitute for Disease ModelingAbstract Background Reactive case detection could be a powerful tool in malaria elimination, as it selectively targets transmission pockets. However, field operations have yet to demonstrate under which conditions, if any, reactive case detection is best poised to push a region to elimination. This study uses mathematical modelling to assess how baseline transmission intensity and local interconnectedness affect the impact of reactive activities in the context of other possible intervention packages. Methods Communities in Southern Province, Zambia, where elimination operations are currently underway, were used as representatives of three archetypes of malaria transmission: low-transmission, high household density; high-transmission, low household density; and high-transmission, high household density. Transmission at the spatially-connected household level was simulated with a dynamical model of malaria transmission, and local variation in vectorial capacity and intervention coverage were parameterized according to data collected from the area. Various potential intervention packages were imposed on each of the archetypical settings and the resulting likelihoods of elimination by the end of 2020 were compared. Results Simulations predict that success of elimination campaigns in both low- and high-transmission areas is strongly dependent on stemming the flow of imported infections, underscoring the need for regional-scale strategies capable of reducing transmission concurrently across many connected areas. In historically low-transmission areas, treatment of clinical malaria should form the cornerstone of elimination operations, as most malaria infections in these areas are symptomatic and onward transmission would be mitigated through health system strengthening; reactive case detection has minimal impact in these settings. In historically high-transmission areas, vector control and case management are crucial for limiting outbreak size, and the asymptomatic reservoir must be addressed through reactive case detection or mass drug campaigns. Conclusions Reactive case detection is recommended only for settings where transmission has recently been reduced rather than all low-transmission settings. This is demonstrated in a modelling framework with strong out-of-sample accuracy across a range of transmission settings while including methodologies for understanding the most resource-effective allocations of health workers. This approach generalizes to providing a platform for planning rational scale-up of health systems based on locally-optimized impact according to simplified stratification.http://link.springer.com/article/10.1186/s12936-017-1903-zMalaria eliminationReactive case detectionStratificationHuman movementMathematical modeling |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jaline Gerardin Caitlin A. Bever Daniel Bridenbecker Busiku Hamainza Kafula Silumbe John M. Miller Thomas P. Eisele Philip A. Eckhoff Edward A. Wenger |
spellingShingle |
Jaline Gerardin Caitlin A. Bever Daniel Bridenbecker Busiku Hamainza Kafula Silumbe John M. Miller Thomas P. Eisele Philip A. Eckhoff Edward A. Wenger Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study Malaria Journal Malaria elimination Reactive case detection Stratification Human movement Mathematical modeling |
author_facet |
Jaline Gerardin Caitlin A. Bever Daniel Bridenbecker Busiku Hamainza Kafula Silumbe John M. Miller Thomas P. Eisele Philip A. Eckhoff Edward A. Wenger |
author_sort |
Jaline Gerardin |
title |
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
title_short |
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
title_full |
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
title_fullStr |
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
title_full_unstemmed |
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
title_sort |
effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study |
publisher |
BMC |
series |
Malaria Journal |
issn |
1475-2875 |
publishDate |
2017-06-01 |
description |
Abstract Background Reactive case detection could be a powerful tool in malaria elimination, as it selectively targets transmission pockets. However, field operations have yet to demonstrate under which conditions, if any, reactive case detection is best poised to push a region to elimination. This study uses mathematical modelling to assess how baseline transmission intensity and local interconnectedness affect the impact of reactive activities in the context of other possible intervention packages. Methods Communities in Southern Province, Zambia, where elimination operations are currently underway, were used as representatives of three archetypes of malaria transmission: low-transmission, high household density; high-transmission, low household density; and high-transmission, high household density. Transmission at the spatially-connected household level was simulated with a dynamical model of malaria transmission, and local variation in vectorial capacity and intervention coverage were parameterized according to data collected from the area. Various potential intervention packages were imposed on each of the archetypical settings and the resulting likelihoods of elimination by the end of 2020 were compared. Results Simulations predict that success of elimination campaigns in both low- and high-transmission areas is strongly dependent on stemming the flow of imported infections, underscoring the need for regional-scale strategies capable of reducing transmission concurrently across many connected areas. In historically low-transmission areas, treatment of clinical malaria should form the cornerstone of elimination operations, as most malaria infections in these areas are symptomatic and onward transmission would be mitigated through health system strengthening; reactive case detection has minimal impact in these settings. In historically high-transmission areas, vector control and case management are crucial for limiting outbreak size, and the asymptomatic reservoir must be addressed through reactive case detection or mass drug campaigns. Conclusions Reactive case detection is recommended only for settings where transmission has recently been reduced rather than all low-transmission settings. This is demonstrated in a modelling framework with strong out-of-sample accuracy across a range of transmission settings while including methodologies for understanding the most resource-effective allocations of health workers. This approach generalizes to providing a platform for planning rational scale-up of health systems based on locally-optimized impact according to simplified stratification. |
topic |
Malaria elimination Reactive case detection Stratification Human movement Mathematical modeling |
url |
http://link.springer.com/article/10.1186/s12936-017-1903-z |
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