Estimation of the serial interval and proportion of pre-symptomatic transmission events of COVID- 19 in Ireland using contact tracing data.

BACKGROUND: The serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms. RESULTS: After data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The median serial interval was 4 days, mean serial interval was 4.0 (95% confidence intervals 3.7, 4.3) days, whilst the 25th and 75th percentiles were 2 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector. CONCLUSIONS: Whilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.

First confirmation by PCR of Jaagsiekte sheep retrovirus in Ireland and prevalence of ovine pulmonary adenocarcinoma in adult sheep at slaughter.

BACKGROUND: Ovine pulmonary adenocarcinoma (OPA), caused by Jaagsiekte sheep retrovirus (JSRV), is characterised by the development of invariably fatal lung tumours primarily in adult sheep. High infection rates and disease prevalence can develop during initial infection of flocks, leading to on-farm economic losses and animal welfare issues in sheep with advanced disease. The disease has been reported in Ireland and is notifiable, but the presence of JSRV has never been confirmed using molecular methods in this country. Additionally, due to the difficulties in ante-mortem diagnosis (especially of latently-infected animals, or those in the very early stages of disease), accurate information regarding national prevalence and distribution is unavailable. This study aimed to confirm the presence of JSRV in Ireland and to obtain estimates regarding prevalence and distribution by means of an abattoir survey utilising gross examination, histopathology, JSRV-specific reverse transcriptase polymerase chain reaction (RT-PCR) and SU protein specific immunohistochemistry (IHC) to examine the lungs of adult sheep. RESULTS: Lungs from 1911 adult sheep were examined macroscopically in the abattoir and 369 were removed for further testing due to the presence of gross lesions of any kind. All 369 were subject to histopathology and RT-PCR, and 46 to IHC. Thirty-one lungs (31/1911, 1.6%) were positive for JSRV by RT-PCR and/or IHC but only ten cases of OPA were confirmed (10/1911, 0.5%) Four lung tumours not associated with JSRV were also identified. JSRV-positive sheep tended to cluster within the same flocks, and JSRV-positive sheep were identified in the counties of Donegal, Kerry, Kilkenny, Offaly, Tipperary, Waterford and Wicklow. CONCLUSIONS: The presence of JSRV has been confirmed in the Republic of Ireland for the first time using molecular methods (PCR) and IHC. In addition, an estimate of OPA prevalence in sheep at slaughter and information regarding distribution of JSRV infection has been obtained. The prevalence estimate appears similar to that of the United Kingdom (UK). Results also indicate that the virus has a diverse geographical distribution throughout Ireland. These data highlights the need for further research to establish national control and monitoring strategies.

Frequentist and Bayesian approaches to prevalence estimation using examples from Johne's disease.

Although frequentist approaches to prevalence estimation are simple to apply, there are circumstances where it is difficult to satisfy assumptions of asymptotic normality and nonsensical point estimates (greater than 1 or less than 0) may result. This is particularly true when sample sizes are small, test prevalences are low and imperfect sensitivity and specificity of diagnostic tests need to be incorporated into calculations of true prevalence. Bayesian approaches offer several advantages including direct computation of range-respecting interval estimates (e.g. intervals between 0 and 1 for prevalence) without the requirement of transformations or large-sample approximations, direct probabilistic interpretation, and the flexibility to model in a straightforward manner the probability of zero prevalence. In this review, we present frequentist and Bayesian methods for animal- and herd-level true prevalence estimation based on individual and pooled samples. We provide statistical methods for detecting differences between population prevalence and frequentist methods for sample size and power calculations. All examples are motivated using Mycobacterium avium subspecies paratuberculosis infection and we provide WinBUGS code for all examples of Bayesian estimation.