COVID19 in Irish Workplaces and Communities - Modelling Outbreaks from Infection data

During 2020-2021, the government of Ireland in line with international recommendations imposed the closure of non-essential trades, services, and commerce. Food plant factories, meat processing plants among others were deemed essential and remained open. During that time, many workers were exposed to outbreaks in their workplaces. Some of the questions arising included if workers will adapt to new safety measures, if those measures could prevent and mitigate workplace outbreaks and, if an outbreak occur in a closed facility, if it will impact community transmission. The most vulnerable workplaces were typically front-line industries, with healthcare and food processing facilities among the hardest hit by Covid-19 infections. To complete the core aims, statistical models were developed for WP1. These models could accurately predict the scale of an outbreak in a meat processing plant based on the infection transmission in the community in the weeks preceding the outbreak and account for patterns in infection spread in both Ireland and worldwide using a ‘behavioural response’ mechanism. In addition to this, vaccine effectiveness was calculated using a method that made use of surveillance data. This demonstrated the strength and limitations of surveillance data. One clear aspect of behaviour in the COVID-19 pandemic has been people’s focus on, and response to, reported or observed infection numbers in their community. WP1 developed a simple model of infectious disease spread in a pandemic situation where people’s behaviour is influenced by the current risk of infection and where this behavioural response acts homeostatically to return infection risk to a certain preferred level. Analysis of worldwide COVID-19 data confirmed the model predictions at both an overall and an individual country level. Building on the findings of the infectious disease spread model, the research team aimed to investigate how individuals adapted their behaviours throughout the pandemic at an individual level, using the number of community cases and the number of contacts reported by cases to the contact-tracing program as a proxy for behavioural response. This work is ongoing at this time. In addition to this, estimations on vaccine effectiveness were calculated using a method that made use of surveillance data. This demonstrated the strength and limitations of surveillance data. There were significant challenges in completing WP1, primarily caused by a difficulty in accessing the required data, however, the primary aims and goals of the work package were achieved and a meaningful body of research was produced on disease spread in specific, controlled environments and among the general population. Our work will certainly inform future pandemics. The main messages are 1) that community transmission can predict the occurrence of outbreaks -suggesting that managers and Public Health officials should work together to reinforce surveillance during peaks of community transmission and 2) high risk settings -like meat factories- can reduce or mitigate outbreaks if they introduce timely protective measures.

Work Package 2: http://hdl.handle.net/10197/25748