Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a review protocol.

Julius Nyerere Odhiambo, Carrie B Dolan
Author Information
  1. Julius Nyerere Odhiambo: Ignite Global Health Research Lab, Global Research Institute, William and Mary, Williamsburg, VA, USA. jnodhiambo@wm.edu.
  2. Carrie B Dolan: Ignite Global Health Research Lab, Global Research Institute, William and Mary, Williamsburg, VA, USA.

Abstract

INTRODUCTION: Severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection that cause Coronavirus disease 2019 (COVID-19) have afflicted millions worldwide. Understanding the underlying spatial and temporal dynamics can help orient timely public health policies and optimize the targeting of non-pharmaceutical interventions and vaccines to the most vulnerable populations, particularly in resource-constrained settings. The review systematically summarises important methodological aspects and specificities of spatial approaches applied to COVID-19 in Africa.
METHODS: Thematically selected keywords will be used to search for refereed studies in the following electronic databases PubMed, SCOPUS, MEDLINE, CINHAL, and Coronavirus Research Database from January 2020 to February 2022. Two independent reviewers will screen the title, abstracts, and full texts against predefined eligibility criteria based on the study's characteristics, methodological relevance, and quality. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 procedures will be adhered to during the reporting process.
DISCUSSION: COVID-19 modeling remains in its infancy, and research is needed to characterize uncertainty and validate various modeling regimes appropriately. It is anticipated that the review will aid spatial, spatio-temporal modeling decisions necessary for mitigating the current and future pandemics.
SYSTEMATIC REVIEW REGISTRATION: CRD42021279767.

Keywords

References

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MeSH Term

Africa
COVID-19
Humans
Pandemics
Review Literature as Topic
SARS-CoV-2

Word Cloud

Created with Highcharts 10.0.0COVID-19willmodelingspatialreviewcoronavirusmethodologicalapproachesAfrica2020spatio-temporalSpatialINTRODUCTION:Severeacuterespiratorysyndrome2SARS-CoV-2infectioncausedisease2019afflictedmillionsworldwideUnderstandingunderlyingtemporaldynamicscanhelporienttimelypublichealthpoliciesoptimizetargetingnon-pharmaceuticalinterventionsvaccinesvulnerablepopulationsparticularlyresource-constrainedsettingssystematicallysummarisesimportantaspectsspecificitiesappliedMETHODS:ThematicallyselectedkeywordsusedsearchrefereedstudiesfollowingelectronicdatabasesPubMedSCOPUSMEDLINECINHALCoronavirusResearchDatabaseJanuaryFebruary2022Twoindependentreviewersscreentitleabstractsfulltextspredefinedeligibilitycriteriabasedstudy'scharacteristicsrelevancequalityPreferredReportingItemsSystematicReviewsMeta-AnalysisPRISMAproceduresadheredreportingprocessDISCUSSION:remainsinfancyresearchneededcharacterizeuncertaintyvalidatevariousregimesappropriatelyanticipatedaiddecisionsnecessarymitigatingcurrentfuturepandemicsSYSTEMATICREVIEWREGISTRATION:CRD42021279767epidemiologicalinformsurveillancecontrol:protocolGeospatialSpatio-temporal

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