In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new ‘phylepic’ visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

This study compared clinico-epidemiological characteristics between Japanese and non-Japanese coronavirus disease 2019 (COVID-19) patients under the pandemic in Japan. We retrospectively analysed nationwide data of hospitalised COVID-19 patients before 31 March 2021. Epidemic curves were constructed to identify the case distribution over time. A total of 28 093 patients were Japanese and 1335 patients were non-Japanese. The major racial and ethnic minorities were East Asians (n = 521), South Asians (n = 260) and Latin Americans (n = 270). Non-Japanese patients were younger and more likely to travel to COVID-19 endemic countries (7.7%), had meals with other people (17.8%), stayed in crowded places (17.9%) and worked mainly in restaurants (6.6%) and service facilities in nightlife businesses (5.2%). In the matched cohorts, we found no clear disparities in time to admission and clinical prognoses. The epidemic curve for non-Japanese patients showed a small peak in the first wave and no definite waves for the second or third waves. Racial and ethnic minorities were at less risk of severe disease but were at a greater risk of COVID-19 exposure; however, the healthcare system in Japan may provide them with equal opportunities to access inpatient care with Japanese. Further research on their social determinants of health in Japan is required.

Previous studies have reported the basic reproduction number (R0) of coronavirus disease from publicly reported data that lack information such as onset of symptoms, presence of importations or known super-spreading events. Using data from the Republic of Korea, we illustrated how estimates of R0 can be biased and provided improved estimates with more detailed data. We used COVID-19 contact trace system in Korea, which can provide symptom onset date and also serial intervals between contacted people. The total R0 was estimated as 2.10 (95% confidence interval (CI) 1.84–2.42). Also, early transmission of COVID-19 differed by regional or social behaviours of the population. Regions affected by a specific church cluster, which showed a rapid and silent transmission under non-official religious meetings, had a higher R0 of 2.40 (95% CI 2.08–2.77).

Japan experienced dengue outbreaks vectored by Aedes albopictus during the Second World War. The probable vector density that caused the largest dengue outbreak in Nagasaki in 1942 was estimated using a mathematical simulation model. The estimated vector density was 15·0–558·0 per person when various assumptions of uncertain parameters were applied, such as proportion of symptomatic cases, vector mortality, and human biting rate of A. albopictus. When the most favourable disease spread conditions, such as a combination of the exclusive human biting rate and the longest vector survival were assumed, the vector density was 15–25 mosquitoes per person. Unusually high vector density due to wartime practices, and the traditional Japanese lifestyle were presumably responsible for the earlier dengue outbreak. If an outbreak occurs in present-day Japan, it is unlikely to spread as much as the previous one, as environmental conditions and human behaviour have changed in a protective manner.

A contact process first posed as a random mapping problem is discussed together with a model for the spread of a rumour through an archaic telephone system. Snowball sampling and the well-known Reed–Frost chain binomial model are also commented on. Our main interest and emphasis is on distributional properties of discrete-time models. Simple combinatorial arguments are used along with a class of discrete distributions originally proposed for catch–recapture sampling.