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Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study

BACKGROUND: COVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention s...

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Autores principales: Mangal, Tara, Whittaker, Charlie, Nkhoma, Dominic, Ng'ambi, Wingston, Watson, Oliver, Walker, Patrick, Ghani, Azra, Revill, Paul, Colbourn, Timothy, Phillips, Andrew, Hallett, Timothy, Mfutso-Bengo, Joseph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300555/
https://www.ncbi.nlm.nih.gov/pubmed/34301651
http://dx.doi.org/10.1136/bmjopen-2020-045196
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author Mangal, Tara
Whittaker, Charlie
Nkhoma, Dominic
Ng'ambi, Wingston
Watson, Oliver
Walker, Patrick
Ghani, Azra
Revill, Paul
Colbourn, Timothy
Phillips, Andrew
Hallett, Timothy
Mfutso-Bengo, Joseph
author_facet Mangal, Tara
Whittaker, Charlie
Nkhoma, Dominic
Ng'ambi, Wingston
Watson, Oliver
Walker, Patrick
Ghani, Azra
Revill, Paul
Colbourn, Timothy
Phillips, Andrew
Hallett, Timothy
Mfutso-Bengo, Joseph
author_sort Mangal, Tara
collection PubMed
description BACKGROUND: COVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity. METHODS: The infection fatality ratios (IFR) were predicted by adjusting reported IFR for China, accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions and increases in health system capacity. FINDINGS: The predicted population-level IFR in Malawi, adjusted for age and comorbidity prevalence, is lower than that estimated for China (0.26%, 95% uncertainty interval (UI) 0.12%–0.69%, compared with 0.60%, 95% CI 0.4% to 1.3% in China); however, the health system constraints increase the predicted IFR to 0.83%, 95% UI 0.49%–1.39%. The interventions implemented in January 2021 could potentially avert 54 400 deaths (95% UI 26 900–97 300) over the course of the epidemic compared with an unmitigated outbreak. Enhanced shielding of people aged ≥60 years could avert 40 200 further deaths (95% UI 25 300–69 700) and halve intensive care unit admissions at the peak of the outbreak. A novel therapeutic agent which reduces mortality by 0.65 and 0.8 for severe and critical cases, respectively, in combination with increasing hospital capacity, could reduce projected mortality to 2.5 deaths per 1000 population (95% UI 1.9–3.6). CONCLUSION: We find the interventions currently used in Malawi are unlikely to effectively prevent SARS-CoV-2 transmission but will have a significant impact on mortality. Increases in health system capacity and the introduction of novel therapeutics are likely to further reduce the projected numbers of deaths.
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spelling pubmed-83005552021-07-23 Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study Mangal, Tara Whittaker, Charlie Nkhoma, Dominic Ng'ambi, Wingston Watson, Oliver Walker, Patrick Ghani, Azra Revill, Paul Colbourn, Timothy Phillips, Andrew Hallett, Timothy Mfutso-Bengo, Joseph BMJ Open Epidemiology BACKGROUND: COVID-19 mitigation strategies have been challenging to implement in resource-limited settings due to the potential for widespread disruption to social and economic well-being. Here we predict the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity. METHODS: The infection fatality ratios (IFR) were predicted by adjusting reported IFR for China, accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions and increases in health system capacity. FINDINGS: The predicted population-level IFR in Malawi, adjusted for age and comorbidity prevalence, is lower than that estimated for China (0.26%, 95% uncertainty interval (UI) 0.12%–0.69%, compared with 0.60%, 95% CI 0.4% to 1.3% in China); however, the health system constraints increase the predicted IFR to 0.83%, 95% UI 0.49%–1.39%. The interventions implemented in January 2021 could potentially avert 54 400 deaths (95% UI 26 900–97 300) over the course of the epidemic compared with an unmitigated outbreak. Enhanced shielding of people aged ≥60 years could avert 40 200 further deaths (95% UI 25 300–69 700) and halve intensive care unit admissions at the peak of the outbreak. A novel therapeutic agent which reduces mortality by 0.65 and 0.8 for severe and critical cases, respectively, in combination with increasing hospital capacity, could reduce projected mortality to 2.5 deaths per 1000 population (95% UI 1.9–3.6). CONCLUSION: We find the interventions currently used in Malawi are unlikely to effectively prevent SARS-CoV-2 transmission but will have a significant impact on mortality. Increases in health system capacity and the introduction of novel therapeutics are likely to further reduce the projected numbers of deaths. BMJ Publishing Group 2021-07-22 /pmc/articles/PMC8300555/ /pubmed/34301651 http://dx.doi.org/10.1136/bmjopen-2020-045196 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
spellingShingle Epidemiology
Mangal, Tara
Whittaker, Charlie
Nkhoma, Dominic
Ng'ambi, Wingston
Watson, Oliver
Walker, Patrick
Ghani, Azra
Revill, Paul
Colbourn, Timothy
Phillips, Andrew
Hallett, Timothy
Mfutso-Bengo, Joseph
Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title_full Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title_fullStr Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title_full_unstemmed Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title_short Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study
title_sort potential impact of intervention strategies on covid-19 transmission in malawi: a mathematical modelling study
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8300555/
https://www.ncbi.nlm.nih.gov/pubmed/34301651
http://dx.doi.org/10.1136/bmjopen-2020-045196
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