Tags

Type your tag names separated by a space and hit enter

Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study.
BMC Med. 2020 10 14; 18(1):324.BM

Abstract

BACKGROUND

The health impact of COVID-19 may differ in African settings as compared to countries in Europe or China due to demographic, epidemiological, environmental and socio-economic factors. We evaluated strategies to reduce SARS-CoV-2 burden in African countries, so as to support decisions that balance minimising mortality, protecting health services and safeguarding livelihoods.

METHODS

We used a Susceptible-Exposed-Infectious-Recovered mathematical model, stratified by age, to predict the evolution of COVID-19 epidemics in three countries representing a range of age distributions in Africa (from oldest to youngest average age: Mauritius, Nigeria and Niger), under various effectiveness assumptions for combinations of different non-pharmaceutical interventions: self-isolation of symptomatic people, physical distancing and 'shielding' (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in African populations, in particular by shifting the distribution of severity risk towards younger ages and increasing the case-fatality ratio. We also present sensitivity analyses for key model parameters subject to uncertainty.

RESULTS

We predicted median symptomatic attack rates over the first 12 months of 23% (Niger) to 42% (Mauritius), peaking at 2-4 months, if epidemics were unmitigated. Self-isolation while symptomatic had a maximum impact of about 30% on reducing severe cases, while the impact of physical distancing varied widely depending on percent contact reduction and R0. The effect of shielding high-risk people, e.g. by rehousing them in physical isolation, was sensitive mainly to residual contact with low-risk people, and to a lesser extent to contact among shielded individuals. Mitigation strategies incorporating self-isolation of symptomatic individuals, moderate physical distancing and high uptake of shielding reduced predicted peak bed demand and mortality by around 50%. Lockdowns delayed epidemics by about 3 months. Estimates were sensitive to differences in age-specific social mixing patterns, as published in the literature, and assumptions on transmissibility, infectiousness of asymptomatic cases and risk of severe disease or death by age.

CONCLUSIONS

In African settings, as elsewhere, current evidence suggests large COVID-19 epidemics are expected. However, African countries have fewer means to suppress transmission and manage cases. We found that self-isolation of symptomatic persons and general physical distancing are unlikely to avert very large epidemics, unless distancing takes the form of stringent lockdown measures. However, both interventions help to mitigate the epidemic. Shielding of high-risk individuals can reduce health service demand and, even more markedly, mortality if it features high uptake and low contact of shielded and unshielded people, with no increase in contact among shielded people. Strategies combining self-isolation, moderate physical distancing and shielding could achieve substantial reductions in mortality in African countries. Temporary lockdowns, where socioeconomically acceptable, can help gain crucial time for planning and expanding health service capacity.

Authors+Show Affiliations

Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK. Kevin.Van-Zandvoort@lshtm.ac.uk.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK. South African Centre for Epidemiological Modelling and Analysis, Stellenbosch University, Stellenbosch, Republic of South Africa.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.No affiliation info availableDepartment of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street,, London, WC1E 7HT, UK.Department of Infectious Disease Epidemiology, Health in Humanitarian Crises Centre, London School of Hygiene & Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

33050951

Citation

van Zandvoort, Kevin, et al. "Response Strategies for COVID-19 Epidemics in African Settings: a Mathematical Modelling Study." BMC Medicine, vol. 18, no. 1, 2020, p. 324.
van Zandvoort K, Jarvis CI, Pearson CAB, et al. Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study. BMC Med. 2020;18(1):324.
van Zandvoort, K., Jarvis, C. I., Pearson, C. A. B., Davies, N. G., Ratnayake, R., Russell, T. W., Kucharski, A. J., Jit, M., Flasche, S., Eggo, R. M., & Checchi, F. (2020). Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study. BMC Medicine, 18(1), 324. https://doi.org/10.1186/s12916-020-01789-2
van Zandvoort K, et al. Response Strategies for COVID-19 Epidemics in African Settings: a Mathematical Modelling Study. BMC Med. 2020 10 14;18(1):324. PubMed PMID: 33050951.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Response strategies for COVID-19 epidemics in African settings: a mathematical modelling study. AU - van Zandvoort,Kevin, AU - Jarvis,Christopher I, AU - Pearson,Carl A B, AU - Davies,Nicholas G, AU - ,, AU - Ratnayake,Ruwan, AU - Russell,Timothy W, AU - Kucharski,Adam J, AU - Jit,Mark, AU - Flasche,Stefan, AU - Eggo,Rosalind M, AU - Checchi,Francesco, Y1 - 2020/10/14/ PY - 2020/04/26/received PY - 2020/09/22/accepted PY - 2020/10/14/entrez PY - 2020/10/15/pubmed PY - 2020/10/29/medline KW - Africa KW - COVID-19 KW - Control KW - Coronavirus KW - Low-income KW - Mathematical model KW - Response KW - SARS-CoV-2 SP - 324 EP - 324 JF - BMC medicine JO - BMC Med VL - 18 IS - 1 N2 - BACKGROUND: The health impact of COVID-19 may differ in African settings as compared to countries in Europe or China due to demographic, epidemiological, environmental and socio-economic factors. We evaluated strategies to reduce SARS-CoV-2 burden in African countries, so as to support decisions that balance minimising mortality, protecting health services and safeguarding livelihoods. METHODS: We used a Susceptible-Exposed-Infectious-Recovered mathematical model, stratified by age, to predict the evolution of COVID-19 epidemics in three countries representing a range of age distributions in Africa (from oldest to youngest average age: Mauritius, Nigeria and Niger), under various effectiveness assumptions for combinations of different non-pharmaceutical interventions: self-isolation of symptomatic people, physical distancing and 'shielding' (physical isolation) of the high-risk population. We adapted model parameters to better represent uncertainty about what might be expected in African populations, in particular by shifting the distribution of severity risk towards younger ages and increasing the case-fatality ratio. We also present sensitivity analyses for key model parameters subject to uncertainty. RESULTS: We predicted median symptomatic attack rates over the first 12 months of 23% (Niger) to 42% (Mauritius), peaking at 2-4 months, if epidemics were unmitigated. Self-isolation while symptomatic had a maximum impact of about 30% on reducing severe cases, while the impact of physical distancing varied widely depending on percent contact reduction and R0. The effect of shielding high-risk people, e.g. by rehousing them in physical isolation, was sensitive mainly to residual contact with low-risk people, and to a lesser extent to contact among shielded individuals. Mitigation strategies incorporating self-isolation of symptomatic individuals, moderate physical distancing and high uptake of shielding reduced predicted peak bed demand and mortality by around 50%. Lockdowns delayed epidemics by about 3 months. Estimates were sensitive to differences in age-specific social mixing patterns, as published in the literature, and assumptions on transmissibility, infectiousness of asymptomatic cases and risk of severe disease or death by age. CONCLUSIONS: In African settings, as elsewhere, current evidence suggests large COVID-19 epidemics are expected. However, African countries have fewer means to suppress transmission and manage cases. We found that self-isolation of symptomatic persons and general physical distancing are unlikely to avert very large epidemics, unless distancing takes the form of stringent lockdown measures. However, both interventions help to mitigate the epidemic. Shielding of high-risk individuals can reduce health service demand and, even more markedly, mortality if it features high uptake and low contact of shielded and unshielded people, with no increase in contact among shielded people. Strategies combining self-isolation, moderate physical distancing and shielding could achieve substantial reductions in mortality in African countries. Temporary lockdowns, where socioeconomically acceptable, can help gain crucial time for planning and expanding health service capacity. SN - 1741-7015 UR - https://www.unboundmedicine.com/medline/citation/33050951/Response_strategies_for_COVID_19_epidemics_in_African_settings:_a_mathematical_modelling_study_ L2 - https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-020-01789-2 DB - PRIME DP - Unbound Medicine ER -