Universidad Peruana Cayetano Heredia

Early warning systems (EWSs) for Chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review

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dc.contributor.author Hussain-Alkhateeb, L.
dc.contributor.author Ramírez, T.R.
dc.contributor.author Kroeger, A.
dc.contributor.author Gozzer Infante, Ernesto Eugenio
dc.contributor.author Runge-Ranzinger, S.
dc.date.accessioned 2021-12-12T20:24:57Z
dc.date.available 2021-12-12T20:24:57Z
dc.date.issued 2021
dc.identifier.uri https://hdl.handle.net/20.500.12866/10256
dc.description.abstract Background Early warning systems (EWSs) are of increasing importance in the context of outbreak-prone diseases such as chikungunya, dengue, malaria, yellow fever, and Zika. A scoping review has been undertaken for all 5 diseases to summarize existing evidence of EWS tools in terms of their structural and statistical designs, feasibility of integration and implementation into national surveillance programs, and the users’ perspective of their applications. Methods Data were extracted from Cochrane Database of Systematic Reviews (CDSR), Google Scholar, Latin American and Caribbean Health Sciences Literature (LILACS), PubMed, Web of Science, and WHO Library Database (WHOLIS) databases until August 2019. Included were studies reporting on (a) experiences with existing EWS, including implemented tools; and (b) the development or implementation of EWS in a particular setting. No restrictions were applied regarding year of publication, language or geographical area. Findings Through the first screening, 11,710 documents for dengue, 2,757 for Zika, 2,706 for chikungunya, 24,611 for malaria, and 4,963 for yellow fever were identified. After applying the selection criteria, a total of 37 studies were included in this review. Key findings were the following: (1) a large number of studies showed the quality performance of their prediction models but except for dengue outbreaks, only few presented statistical prediction validity of EWS; (2) while entomological, epidemiological, and social media alarm indicators are potentially useful for outbreak warning, almost all studies focus primarily or exclusively on meteorological indicators, which tends to limit the prediction capacity; (3) no assessment of the integration of the EWS into a routine surveillance system could be found, and only few studies addressed the users’ perspective of the tool; (4) almost all EWS tools require highly skilled users with advanced statistics; and (5) spatial prediction remains a limitation with no tool currently able to map high transmission areas at small spatial level. Conclusions In view of the escalating infectious diseases as global threats, gaps and challenges are significantly present within the EWS applications. While some advanced EWS showed high prediction abilities, the scarcity of tool assessments in terms of integration into existing national surveillance systems as well as of the feasibility of transforming model outputs into local vector control or action plans tends to limit in most cases the support of countries in controlling disease outbreaks en_US
dc.language.iso eng
dc.publisher Public Library of Science
dc.relation.ispartofseries PLoS Neglected Tropical Diseases
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject chikungunya en_US
dc.subject dengue en_US
dc.subject disease resistance en_US
dc.subject disease surveillance en_US
dc.subject disease transmission en_US
dc.subject early warning system en_US
dc.subject entomology en_US
dc.subject epidemic en_US
dc.subject geographic distribution en_US
dc.subject hospitalization en_US
dc.subject human en_US
dc.subject malaria en_US
dc.subject predictive value en_US
dc.subject Review en_US
dc.subject sensitivity and specificity en_US
dc.subject social media en_US
dc.subject yellow fever en_US
dc.subject Zika fever en_US
dc.title Early warning systems (EWSs) for Chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review en_US
dc.type info:eu-repo/semantics/review
dc.identifier.doi https://doi.org/10.1371/journal.pntd.0009686
dc.relation.issn 1935-2735


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