First back-calculation and infection fatality multiplier estimate of the hidden prevalence of COVID-19 in Ireland.

BACKGROUND: To date computer models with multiple assumptions have focussed on predicting the incidence of symptomatic cases of COVID-19. Given emerging vaccines, the aim of this study was to provide simple methods for estimating the hidden prevalence of asymptomatic cases and levels of herd immunity to aid future immunization policy and planning. We applied the method in Ireland. METHODS: For large scale epidemics, indirect models for estimating prevalence have been developed. One such method is the benchmark multiplier method. A further method is back-calculation, which has been used successfully to produce estimates of the scale of a HIV infected population. The methods were applied from March to October 2020 and are applicable globally. RESULTS: Results demonstrated that the number of infected individuals was at least twice and possibly six times the number identified through testing. Our estimates ranged from ∼100 000 to 375 000 cases giving a ratio of 1-6 hidden cases for every known case within the study time frame. While both methods are subject to assumptions and limitations, it was interesting to observe that estimates corroborated government statements noting that 80% of people testing positive were asymptomatic. CONCLUSIONS: As Europe has now endured several epidemic waves with the emergence globally of new variants, it essential that both policy makers and the public are aware of the scale of the hidden epidemic that may surround them. The need for social distancing is as important as ever as we await global immunization rollout.

The second wave: estimating the hidden asymptomatic prevalence of COVID-19 in Ireland as we plan for imminent immunisation.

Since the first case of COVID-19 in Ireland was recorded policy makers have introduced mitigation measures to control the spread of infection. Infection is spread by both known cases and hidden, undetected asymptomatic cases.  Asymptomatic individuals are people who transmit the virus but display no clinical symptoms. Current evidence reveals that this population is a major contributing factor to the spread of the disease. There is little or no knowledge of the scale of the hidden prevalence of all infections both asymptomatic and symptomatic in Ireland. Furthermore, as governments plan for the roll out of imminent immunisation programmes, the need to know the scale of the hidden prevalence and hence knowledge of the level of immunisation required is essential. We describe and analyse the numbers of reported cases of COVID-19 in Ireland from the first case in February 2020 to mid-December 2020. Using the method of back-calculation we provide estimates of the asymptomatic prevalence of cases from June to December 2020. The descriptive analysis highlighted two epidemic waves of known cases in the time period. Wave two from June to December included twice as many cases as wave one and cases were significantly younger. The back-calculation estimates of asymptomatic prevalence during this time period revealed that for every case known there was an additional unknown case and total prevalence in wave two was estimated to be approximately 95,000 as opposed to the reported 48,390 cases. As prevalence in wave two is known to be spreading within and from younger age groups the role of mixing patterns on spread needs to be disseminated to the wider public to adequately inform them how personal modifications in behaviour can contribute to the control of the epidemic. While universally imposed lockdowns and mitigation measures may be essential, personal behavioural mixing choices are powerful protectors.

Using Client's Routine Urinalysis Records From Multiple Treatment Systems to Model Five-Year Opioid Substitution Treatment Outcomes.

BACKGROUND: At global, national, and local level, the need for ongoing, timely and cost efficient, comprehensive drug treatment monitoring, and evaluation systems have clearly been well recognized. OBJECTIVES: To test the feasibility of linking laboratory data and client intake data and its usefulness for modeling retrospectively, for the first time, 5-year longitudinal drug treatment outcomes in an Irish opiate treatment setting. METHODS: A multisite, retrospective, longitudinal cohort study was implemented to evaluate outcomes for opiate users based on 1.7 million routine urinalysis results collected from 4,518 individuals presenting for opioid substitution treatment in Ireland from January 2006 to December 2010. RESULTS: Analysis of opiates, cocaine, benzodiazepine, and cannabis use at treatment intake, 6 months and at 1-5 year follow-ups revealed differences in urinalysis protocols; significant differences in age of first drug use between those using and not using opiates at 5 years; significant decreases in opiate use; increases in benzodiazepine use and significant increasing effects of concurrent cocaine and benzodiazepine use on the odds of using opiates. Time series analysis of weekly proportions opiate positive predicted 16% (95% confidence interval: 7%-25%) of clients would be opiate positive 5 years postinitial intake. CONCLUSIONS IMPORTANCE: Underutilized urinalysis data can be used to address the need for cost effective, efficient evidence of drug-treatment outcomes across time, place, and systems. Linking and matching the cross-sectional data across sites and times also revealed where improvements in electronic records could be made.

Measuring and modelling body mass index among a cohort of urban children living with disadvantage.

AIM: To report on baseline outcomes of body mass index, eating habits and physical activity of a cohort of urban disadvantaged children from a longitudinal evaluation of a school based, health promoting initiative. BACKGROUND: The healthy schools programme was developed for implementation in schools located in disadvantaged areas of Dublin, Ireland. DESIGN: A prospective, cohort study design was implemented. METHOD: A 3-year longitudinal evaluation was conducted in five intervention and two comparison schools between 2009-2011. Data were collected on each participating child to determine their eating habits, levels of physical activity and body mass index at year 1 (baseline), year 2 and year 3. Independent t-tests were used to compare mean values, chi-square and Fishers exact tests were used to compare proportions at baseline. RESULTS: Participation rates were over 50%. Older children reported eating on average more fruit and vegetables than younger children; breakfast was often eaten on the way to, or in school and in one age group 16.7% of intervention children reported they did not eat breakfast that day. Levels of physical activity varied with over 70% of younger children stating they never played a sport. In intervention schools over one quarter of all children were either overweight or obese. A comparison was conducted between the proportion of 9-year olds overweight and obese in our disadvantaged cohort and a national random sample of 8500 9-year olds and no important differences were observed. CONCLUSION: Baseline results indicate that body mass index rates particularly among pre adolescent, urban disadvantaged girls are of concern.