An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020-2021.


Journal

PLoS neglected tropical diseases
ISSN: 1935-2735
Titre abrégé: PLoS Negl Trop Dis
Pays: United States
ID NLM: 101291488

Informations de publication

Date de publication:
03 2022
Historique:
received: 20 07 2021
accepted: 01 02 2022
revised: 16 03 2022
pubmed: 5 3 2022
medline: 5 4 2022
entrez: 4 3 2022
Statut: epublish

Résumé

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued, indicating the pandemic fatigue in the country.

Identifiants

pubmed: 35245285
doi: 10.1371/journal.pntd.0010228
pii: PNTD-D-21-01087
pmc: PMC8926206
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0010228

Subventions

Organisme : FIC NIH HHS
ID : D43 TW007124
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG059307
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB025022
Pays : United States

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Amna Tariq (A)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Tsira Chakhaia (T)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Sushma Dahal (S)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Alexander Ewing (A)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Xinyi Hua (X)

Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia, United States of America.

Sylvia K Ofori (SK)

Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia, United States of America.

Olaseni Prince (O)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Argita D Salindri (AD)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Ayotomiwa Ezekiel Adeniyi (AE)

Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, Georgia, United States of America.

Juan M Banda (JM)

Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, Georgia, United States of America.

Pavel Skums (P)

Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, Georgia, United States of America.

Ruiyan Luo (R)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Leidy Y Lara-Díaz (LY)

Centro de Investigación en Ingeniería Matemática (CI2MA) and Departamento de Ingeniería Matemática, Universidad de Concepción, Concepción, Chile.

Raimund Bürger (R)

Centro de Investigación en Ingeniería Matemática (CI2MA) and Departamento de Ingeniería Matemática, Universidad de Concepción, Concepción, Chile.

Isaac Chun-Hai Fung (IC)

Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia, United States of America.

Eunha Shim (E)

Department of Mathematics and Integrative Institute of Basic Sciences, Soongsil University, Seoul, Republic of Korea.

Alexander Kirpich (A)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

Anuj Srivastava (A)

Department of Statistics, Florida State University, Tallahassee, Florida, United States of America.

Gerardo Chowell (G)

Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, United States of America.

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Classifications MeSH