Data Sharing in Southeast Asia During the First Wave of the Covid-19 Pandemic

Datos Bibliográficos

ID22068375
AutoresArianna Maever L Amit (0000-0003-4571-400X, Johns Hopkins University, autor de correspondencia), Veincent Christian Filipino Pepito (0000-0001-5391-3784, Ateneo de Manila University), Bernardo Gutiérrez (University of Oxford), Thomas Rawson (0000-0001-8182-4279, University of Oxford, autor de correspondencia)
Año2021
Volumen9
Páginas662842-662842
Fecha de publicación2021-06-16
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2021.662842
PMID34222173
OpenAlexW3172570741
IdiomaEN
Referencias citadas46

Background: When a new pathogen emerges, consistent case reporting is critical for public health surveillance. Tracking cases geographically and over time is key for understanding the spread of an infectious disease and effectively designing interventions to contain and mitigate an epidemic. In this paper we describe the reporting systems on COVID-19 in Southeast Asia during the first wave in 2020, and highlight the impact of specific reporting methods. Methods: We reviewed key epidemiological variables from various sources including a regionally comprehensive dataset, national trackers, dashboards, and case bulletins for 11 countries during the first wave of the epidemic in Southeast Asia. We recorded timelines of shifts in epidemiological reporting systems and described the differences in how epidemiological data are reported across countries and timepoints. Results: Our findings suggest that countries in Southeast Asia generally reported precise and detailed epidemiological data during the first wave of the pandemic. Changes in reporting rarely occurred for demographic data, while reporting shifts for geographic and temporal data were frequent. Most countries provided COVID-19 individual-level data daily using HTML and PDF, necessitating scraping and extraction before data could be used in analyses. Conclusion: Our study highlights the importance of more nuanced analyses of COVID-19 epidemiological data within and across countries because of the frequent shifts in reporting. As governments continue to respond to impacts on health and the economy, data sharing also needs to be prioritised given its foundational role in policymaking, and in the implementation and evaluation of interventions

Alternative medicine · Data sharing · Disease · Environmental health · Geography · Pandemic · Pathology · Psychological intervention · Public health · Southeast asia · Timeline · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · History · Medicine · Epidemiology