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 st...
Main Authors: | , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
BMJ Publishing Group
2021-07-01
|
Series: | BMJ Open |
Online Access: | https://bmjopen.bmj.com/content/11/7/e045196.full |
id |
doaj-a891689a3ba64f0f849d24e3f11a2eef |
---|---|
record_format |
Article |
spelling |
doaj-a891689a3ba64f0f849d24e3f11a2eef2021-08-07T16:33:22ZengBMJ Publishing GroupBMJ Open2044-60552021-07-0111710.1136/bmjopen-2020-045196Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling studyPaul Revill0Oliver Watson1Andrew Phillips2Azra Ghani3Patrick Walker4Timothy Hallett5Dominic Nkhoma6Tara Mangal7Charlie Whittaker8Wingston Ng'ambi9Timothy Colbourn10Joseph Mfutso-Bengo11Centre for Health Economics, University of York, York, UKInfectious Disease Epidemiology, Imperial College London, London, UKHIV Epidemiology and Biostatistics Group, University College London, London, UKInfectious Disease Epidemiology, Imperial College London, London, UKInfectious Disease Epidemiology, Imperial College London, London, UKInfectious Disease Epidemiology, Imperial College London, London, UKCollege of Medicine, University of Malawi, Lilongwe, MalawiInfectious Disease Epidemiology, Imperial College London, London, UKInfectious Disease Epidemiology, Imperial College London, London, UKCollege of Medicine, University of Malawi, Lilongwe, MalawiInstitute for Global Health, University College London, London, UKCollege of Medicine, University of Malawi, Lilongwe, MalawiBackground 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.https://bmjopen.bmj.com/content/11/7/e045196.full |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Paul Revill Oliver Watson Andrew Phillips Azra Ghani Patrick Walker Timothy Hallett Dominic Nkhoma Tara Mangal Charlie Whittaker Wingston Ng'ambi Timothy Colbourn Joseph Mfutso-Bengo |
spellingShingle |
Paul Revill Oliver Watson Andrew Phillips Azra Ghani Patrick Walker Timothy Hallett Dominic Nkhoma Tara Mangal Charlie Whittaker Wingston Ng'ambi Timothy Colbourn Joseph Mfutso-Bengo Potential impact of intervention strategies on COVID-19 transmission in Malawi: a mathematical modelling study BMJ Open |
author_facet |
Paul Revill Oliver Watson Andrew Phillips Azra Ghani Patrick Walker Timothy Hallett Dominic Nkhoma Tara Mangal Charlie Whittaker Wingston Ng'ambi Timothy Colbourn Joseph Mfutso-Bengo |
author_sort |
Paul Revill |
title |
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_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_sort |
potential impact of intervention strategies on covid-19 transmission in malawi: a mathematical modelling study |
publisher |
BMJ Publishing Group |
series |
BMJ Open |
issn |
2044-6055 |
publishDate |
2021-07-01 |
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. |
url |
https://bmjopen.bmj.com/content/11/7/e045196.full |
work_keys_str_mv |
AT paulrevill potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT oliverwatson potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT andrewphillips potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT azraghani potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT patrickwalker potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT timothyhallett potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT dominicnkhoma potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT taramangal potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT charliewhittaker potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT wingstonngambi potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT timothycolbourn potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy AT josephmfutsobengo potentialimpactofinterventionstrategiesoncovid19transmissioninmalawiamathematicalmodellingstudy |
_version_ |
1721216980116045824 |