Data analysis.
infection, infections
INFECTION, INFECTIONS, REGRESSIONS
All quantitative analysis was conducted in SAS v9.4 (SAS Institute Inc., Cary, NC). Using the unique project identifiers, respondent names, and parenting group location information, the questionnaires for each respondent were linked to their demographic information.We created a timepoint variable, dividing the study period around the observed waves of COVID-19 Zambia. Timepoint 1 (T1) represents August to December 2020, as cases were rising in the country and before the first infection peak. Timepoint 2 (T2) represents January to March 2021, as the first peak in infections was recorded and eventually receded. Timepoint 3 (T3) represents a “recovery” period, when cases from the January peak receded, and there was little incidence of infection in Zambia. Timepoint 4 (T4) represents the second peak of cases between July and September of 2021 (COVID-19 case trends, government policy, and guidance in Zambia between March 2020 and March 2021.We analyzed primary outcome variables including perceived risk of contracting COVID-19, attendance at community gatherings, perceived size of such gatherings, and mask wearing. We present frequencies and means for these outcomes. We ran logistic regressions to calculate crude and adjusted odds ratios (aOR). Adjusted models control for the following variables: gathering type, location, number of attendees, district, and timepoint, and where relevant they control for respondents’ demographic information.We conducted sensitivity analysis to identify differences between linked and unlinked respondents: we conducted χ