A COVID-19 outbreak in a food processing factory and its mitigation strategies, Samut Sakhon province, Thailand, 2020-2021

Abstract

 In January 2020, Department of Disease Control (DDC) operations team was notified that 959 cases of coronavirus disease 2019 (COVID-19) were detected by reverse-transcriptase polymerase chain reaction (RT-PCR) in a food processing factory in Samut Sakhon, Thailand. To describe epidemiological characteristics, we performed active case finding and contact tracing by interviewing the cases, reviewing laboratory results and studying the factory’s employee database. A confirmed case was defined as a person working in the factory with positive RT-PCR result for COVID-19 while a probable case was a person with a positive serum IgG or IgM antibody against SARS-CoV-2. Nobody received COVID-19 vaccination at the time of the study. An environmental study was conducted. A cross-sectional cohort study, using Poisson regression with robust standard error, in the production department (n=2,811) was performed to identify risk factors of COVID-19 infection. A total of 1,663 cases were identified (overall attack rate=42.9%). The majority of the cases were Myanmar migrant workers (87.2%). The median age was 32 years old (Q1, Q3=26, 39). No death was observed. Most cases occurred in the production department (attack rate=54.2%). Working in the production line (adjusted risk ratio (aRR) 1.63, 95% CI=1.05-2.51), working in the night shift (aRR 1.27, 95% CI =1.14-1.42), being migrant (aRR 1.90, 95% CI=1.54-2.34) and being female (aRR 1.64, 95% CI =1.39-1.92) served as main risk factors. Close proximity (<2 feet), prolonged shift work and high humidity were likely to facilitate disease spreading in the production department. Relaxed control measures were identified during night shift was likely to be another risk factor. Moreover, migrant workers’ communities were overcrowded and the living conditions were of poor hygiene. COVID-19 outbreak in a large-size factory was a significant public health concern as it might cause a super spreading event and served as sources for further outbreaks in communities. Interventions that help facilitate early detection of cases and help modify the outbreak-prone working environment should be promptly implemented. Creating a workplace-accommodation bubble during active factory outbreaks and changing flow and production environment can help reduce the risk of community outbreaks while helping essential businesses continue to function.