We used primary care data to retrospectively describe the entry, spread, and impact of COVID-19 in a remote rural community and the associated risk factors and challenges faced by the healthcare team. Generalized linear models were fitted to assess the relationship between age, sex, period, risk group status, symptom duration, post-COVID illness, and disease severity. Social network and cluster analyses were also used. The first six cases, including travel events and a social event in town, contributed to early infection spread. About 351 positive cases were recorded and 6% of patients experienced two COVID-19 episodes in the 2.5-year study period. Five space-time case clusters were identified. One case, linked with the social event, was particularly central in its contact network. The duration of disease symptoms was driven by gender, age, and risk factors. The probability of suffering severe disease increased with symptom duration and decreased over time. About 27% and 23% of individuals presented with residual symptoms and post-COVID illness, respectively. The probability of developing a post-COVID illness increased with age and the duration of COVID-associated symptoms. Carefully registered primary care data may help optimize infection prevention and control efforts and upscale local healthcare capacities in vulnerable rural communities.
Keywords: SARS-CoV-2; disease impact; long COVID; outbreak dynamics; rural healthcare.