Outbreaks in care homes may lead to substantial disease burden if not mitigated.

The number of COVID-19 outbreaks reported in UK care homes rose rapidly in early March of 2020. Owing to the increased co-morbidities and therefore worse COVID-19 outcomes for care home residents, it is important that we understand this increase and its future implications. We demonstrate the use of an SIS model where each nursing home is an infective unit capable of either being susceptible to an outbreak (S) or in an active outbreak (I).

Using statistics and mathematical modelling to understand infectious disease outbreaks: COVID-19 as an example.

During an infectious disease outbreak, biases in the data and complexities of the underlying dynamics pose significant challenges in mathematically modelling the outbreak and designing policy. Motivated by the ongoing response to COVID-19, we provide a toolkit of statistical and mathematical models beyond the simple SIR-type differential equation models for analysing the early stages of an outbreak and assessing interventions. In particular, we focus on parameter estimation in the presence of known biases in the data, and the effect of non-pharmaceutical interventions in enclosed subpopulations, such as households and care homes.

[Coxiella burnetii infections (Q fever) in animals and humans in Poznan and Leszno districts detected by serodiagnosis].

In Poznań and Leszno districts, serological survey of Q fever among cattle and sheep have been performed since 1973. Coxiella burnetii infections have not been detected until 1985. During this period 28,272 blood samples derived from cattle and sheep have been tested.

Epidemic of Q fever in Leszno district in Poland.

In 1988 an epidemic of Q fever was detected in Leszno district. During 1973-1985 all 28,066 cattle tested for C. burnetii antibodies were found to be negative.