Evidence map›Paper›PMID 39845719›Full record

ArticleRoyal Society open science2025

SARS-CoV-2 transmission dynamics in Mozambique and Zimbabwe during the first 3 years of the pandemic.

Roselyn F Kaondera-Shava, Marta Galanti, Matteo Perini, Jiyeon Suh, Shannon M Farley, Sergio Chicumbe, Ilesh Jani, Annette Cassy, Ivalda Macicame, Naisa Manafe and 2 more

Abstract read
In one paragraph

Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Data assimilation for estimating time-varying reproduction numbers.Journal of the Royal Society, Interface · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Roselyn F Kaondera-ShavaDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.ORCID https://orcid.org/0000-0002-4254-9777
Marta GalantiDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.ORCID https://orcid.org/0000-0002-9060-1250
Matteo PeriniDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Jiyeon SuhDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Shannon M FarleyDepartment of Population and Family Health, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Sergio ChicumbeInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, Mozambique.
Ilesh JaniInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, Mozambique.
Annette CassyInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, Mozambique.
Ivalda MacicameInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, Mozambique.
Naisa ManafeInstituto Nacional de Saúde (INS) EN1, Bairro da Vila-Parcela n 3943, Distrito de Marracuene, Maputo, C.P. 264, Mozambique.
Wafaa El-SadrDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
Jeffrey ShamanDepartment of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.

Funding

Quantifying Error Growth to Improve Infectious Disease Forecast AccuracyR01AI163023 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI JEFFREY L SHAMAN · 2021 to 2026
$3.3M
NIAID NIH HHS R01 AI163023
6 · The paper itself

Abstract

The 2019 emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread created a public health emergency of international concern. However, the impact of the pandemic in Sub-Saharan Africa, as documented in cases, hospitalizations and deaths, appears far lower than in the Americas, Europe and Asia. Characterization of the transmission dynamics is critical for understanding how SARS-CoV-2 spreads and the true scale of the pandemic. Here, to better understand SARS-CoV-2 transmission dynamics in two southern African countries, Mozambique and Zimbabwe, we developed a dynamic model-Bayesian inference system to estimate key epidemiological parameters, namely the transmission and ascertainment rates. Total infection burdens (reported and unreported) during the first 3 years of the pandemic were reconstructed using a model-inference approach. Transmission rates rose with each successive wave, which aligns with observations in other continents. Ascertainment rates were found to be low and consistent with other African countries. Overall, the estimated disease burden was higher than the documented cases, indicating a need for improved reporting and surveillance. These findings aid understanding of COVID-19 disease and respiratory virus transmission dynamics in two African countries little investigated to date and can help guide future public health planning and control strategies.

Indexed as

ascertainment rateBayesian inferenceCOVID-19dynamic modelSARS-CoV-2transmission rate

Identifiers

PMID39845719
PMCPMC11750399

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.