How do field epidemiologists learn? A protocol for a qualitative inquiry into learning in field epidemiology training programmes.

INTRODUCTION: COVID-19 underscored the importance of field epidemiology training programmes (FETPs) as countries struggled with overwhelming demands. Experts are calling for more field epidemiologists with better training. Since 1951, FETPs have been building public health capacities across the globe, yet explorations of learning in these programmes are lacking. This qualitative study will (1) describe approaches to training field epidemiologists in FETP; (2) describe strategies for learning field epidemiology among FETP trainees and (3) explain the principles and practices aligning training approaches with learning strategies in FETP. METHODS AND ANALYSIS: The research design, implementation and interpretation are collaborative efforts with FETP trainers. Data collection will include interviews with FETP trainers and trainees and participant observations of FETP training and learning events in four FETP in the Western Pacific Region. Data analysis will occur in three phases: (1) we will use the constant comparison method of Charmaz's grounded theory during open coding to identify and prioritise categories and properties in the data; (2) during focused coding, we will use constant comparison and Polkinghorne's analysis of narratives, comparing stories of prioritised categories, to fill out properties of those categories and (3) we will use Polkinghorne's narrative analysis to construct narratives that reflect domains of interest, identifying correspondence among Carr and Kemmis's practices, understandings and situations to explain principles and processes of learning in FETP. ETHICS AND DISSEMINATION: We have obtained the required ethics approvals to conduct this research at The Australian National University (2021/771) and Taiwan's Ministry of Health and Welfare (112206). Data will not be available publicly, but anonymised findings will be shared with FETP for collaborative interpretation. Ultimately, findings and interpretations will appear in peer-reviewed journals and conferences.

Transmission of COVID-19 in Nightlife, Household, and Health Care Settings in Tokyo, Japan, in 2020.

Importance: There have been few studies on the heterogeneous interconnection of COVID-19 outbreaks occurring in different social settings using robust, surveillance epidemiological data. Objectives: To describe the characteristics of COVID-19 transmission within different social settings and to evaluate settings associated with onward transmission to other settings. Design, Setting, and Participants: This is a case series study of laboratory-confirmed COVID-19 cases in Tokyo between January 23 and December 5, 2020, when vaccination was not yet implemented. Using epidemiological investigation data collected by public health centers, epidemiological links were identified and classified into 7 transmission settings: imported, nightlife, dining, workplace, household, health care, and other. Main Outcomes and Measures: The number of cases per setting and the likelihood of generating onward transmissions were compared between different transmission settings. Results: Of the 44 054 confirmed COVID-19 cases in this study, 25 241 (57.3%) were among male patients, and the median (IQR) age of patients was 36 (26-52) years. Transmission settings were identified in 13 122 cases, including 6768 household, 2733 health care, and 1174 nightlife cases. More than 6600 transmission settings were detected, and nightlife (72 of 380 [18.9%]; P < .001) and health care (119 [36.2%]; P < .001) settings were more likely to involve 5 or more cases than dining, workplace, household, and other settings. Nightlife cases appeared in the earlier phase of the epidemic, while household and health care cases appeared later. After adjustment for transmission setting, sex, age group, presence of symptoms, and wave, household and health care cases were less likely to generate onward transmission compared with nightlife cases (household: adjusted odds ratio, 0.03; 95% CI, 0.02-0.05; health care: adjusted odds ratio, 0.57; 95% CI, 0.41-0.79). Household settings were associated with intergenerational transmission, while nonhousehold settings mainly comprised transmission between the same age group. Among 30 932 cases without identified transmission settings, cases with a history of visiting nightlife establishments were more likely to generate onward transmission to nonhousehold settings (adjusted odds ratio, 5.30 [95% CI, 4.64-6.05]; P < .001) than those without such history. Conclusions and Relevance: In this case series study, COVID-19 cases identified in nightlife settings were associated with a higher likelihood of spreading COVID-19 than household and health care cases. Surveillance and interventions targeting nightlife settings should be prioritized to disrupt COVID-19 transmission, especially in the early stage of an epidemic.