Simulation-based assessment of model selection criteria during the application of benchmark dose method to quantal response data.

BACKGROUND: To employ the benchmark dose (BMD) method in toxicological risk assessment, it is critical to understand how the BMD lower bound for reference dose calculation is selected following statistical fitting procedures of multiple mathematical models. The purpose of this study was to compare the performances of various combinations of model exclusion and selection criteria for quantal response data. METHODS: Simulation-based evaluation of model exclusion and selection processes was conducted by comparing validity, reliability, and other model performance parameters. Three different empirical datasets for different chemical substances were analyzed for the assessment, each having different characteristics of the dose-response pattern (i.e. datasets with rich information in high or low response rates, or approximately linear dose-response patterns). RESULTS: The best performing criteria of model exclusion and selection were different across the different datasets. Model averaging over the three models with the lowest three AIC (Akaike information criteria) values (MA-3) did not produce the worst performance, and MA-3 without model exclusion produced the best results among the model averaging. Model exclusion including the use of the Kolmogorov-Smirnov test in advance of model selection did not necessarily improve the validity and reliability of the models. CONCLUSIONS: If a uniform methodological suggestion for the guideline is required to choose the best performing model for exclusion and selection, our results indicate that using MA-3 is the recommended option whenever applicable.

Age dependence of the natural history of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): an analysis of Diamond Princess data.

BACKGROUND: Following an outbreak of coronavirus disease 2019 (COVID-19) on the cruise ship Diamond Princess, passengers and crew were followed-up to determine prognosis. This study examined the epidemiological determinants of COVID-19 natural history using these follow-up data. METHODS: Infection status, diagnosis, clinical symptoms and prognosis were analysed for all passengers and crew members on the Diamond Princess. In addition, the risk of infection associated with exposure within cabin rooms, as well as the risks of various clinical manifestations of disease, along with their epidemiological determinants, were analysed. RESULTS: The adjusted odds ratio (aOR) of infection for individuals tested by polymerase chain reaction on or after 12 February 2020 compared with individuals tested before this date was 0.53 [95% confidence interval (CI) 0.39-0.72], reflecting decreased transmission during onboard quarantine. Among infected individuals, older age was associated with elevated odds of symptomatic illness (aOR 1.01, 95% CI 1.00-1.02), severe disease (aOR 1.08, 95% CI 1.05-1.12) and death (aOR 1.12, 95% CI 1.05-1.21). CONCLUSIONS: Severe COVID-19 disease, death and symptomatic illness were more frequent among older individuals on the Diamond Princess. Older elderly cases (age ≥80 years) had the highest risks of severe disease and death. Inter-room transmission was prevented successfully by the onboard quarantine.

An investigation of a measles outbreak in Japan and China, Taiwan, China, March-May 2018.

OBJECTIVE: To investigate a measles outbreak that spread to Japan and China, Taiwan, China during March-May 2018, exploring the characteristics of the super-spreading event. METHODS: A contact investigation of the index case and reconstruction of the epidemiological dynamics of measles transmission were conducted. Employing a mathematical model, the effective reproduction number was estimated for each generation of cases. RESULTS AND DISCUSSION: A single index case gave rise to a total of 38 secondary cases, 33 in Japan and five in China, Taiwan, China. Subsequent chains of transmission were observed in highly vaccinated populations in both Japan and China, Taiwan, China. The effective reproduction number of the second generation was > 1 for both Japan and China, Taiwan, China. In Japan, the reproduction number was estimated to be < 1 during the third generation. Vaccination of susceptible individuals is essential to prevent secondary and tertiary transmission events.

Real Time Forecasting of Measles Using Generation-dependent Mathematical Model in Japan, 2018.

BACKGROUND: Japan experienced a multi-generation outbreak of measles from March to May, 2018. The present study aimed to capture the transmission dynamics of measles by employing a simple mathematical model, and also forecast the future incidence of cases. METHODS: Epidemiological data that consist of the date of illness onset and the date of laboratory confirmation were analysed. A functional model that captures the generation-dependent growth patterns of cases was employed, while accounting for the time delay from illness onset to diagnosis. RESULTS: As long as the number of generations is correctly captured, the model yielded a valid forecast of measles cases, explicitly addressing the reporting delay. Except for the first generation, the effective reproduction number was estimated by generation, assisting evaluation of public health control programs. CONCLUSIONS: The variance of the generation time is relatively limited compared with the mean for measles, and thus, the proposed model was able to identify the generation-dependent dynamics accurately during the early phase of the epidemic. Model comparison indicated the most likely number of generations, allowing us to assess how effective public health interventions would successfully prevent the secondary transmission.