Back

Variation in social contact levels and changes during the COVID-19 pandemic by occupation and socio-economic status in east Zimbabwe

Ayling, S.; Nyamukapa, C.; Maswera, R.; Moorhouse, L.; Morris, R.; Moyo, B.; Melegaro, A.; Mugurungi, O.; Fry, H.; Wise, S.; Harling, G.; Gregson, S.

2026-10-06 public and global health
10.64898/2026.10.04.26364721 medRxiv
Show abstract

Background: COVID-19 movement restrictions reduced social contact worldwide, curbing viral spread but with unequal economic consequences where social safety nets are limited. Little evidence exists on how these impacts varied by occupation, wealth and age in resource-constrained settings. This paper examined pre-pandemic contact and lockdown-related change. Methods: The paper documents analysis of a population-representative survey (N=8,499) in Manicaland, Zimbabwe, during April-May 2021, capturing typical weekday contacts before and during the first COVID-19 lockdown. Negative binomial regression models assessed pre-lockdown contact counts by socio-economic characteristics, overall and by place (home, school, work, transport, entertainment); linear regression assessed predictors of lockdown declines. Results: Pre-COVID-19, respondents reported a median of 12 daily contacts (interquartile range [IQR] 4-47), with higher counts among manual labourers (incidence rate ratio [IRR] 2.21, 95% confidence interval [CI] 2.00, 2.44), retail and public sector workers (IRR 2.33, 95%CI 2.09, 2.60) and students (IRR 2.59, 95%CI 2.38, 2.82), males, wealthier respondents, under-30s, and urban and agricultural estate residents. Counts were highest in schools. During lockdown, contacts fell across all subgroups to a median of 8 (IQR 4-28). Declines were greatest among those with most pre-COVID-19 contacts: urban (mean -17.5, 95%CI -19.53, -15.37) and agricultural estate residents (-18.1, 95%CI -19.99, -16.13), students and teachers (-17.7, 95%CI -19.82, -15.59), males and 30-44 year olds. Drops were greatest in schools and on transport. Conclusion: Reductions in contact under blanket lockdown varied markedly between subgroups and places in Manicaland, Zimbabwe. Selectively targeting high-contact groups might have achieved similar transmission reductions while limiting economic damage, holding lessons for similar settings.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.