Database of epidemic trends and control measures during the first wave of COVID-19 in mainland China.

OBJECTIVES: In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China. METHODS: From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces. RESULTS: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic. CONCLUSIONS: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.

Genomic epidemiology of penicillin-non-susceptible Streptococcus pneumoniae.

Penicillin-non-susceptible Streptococcus pneumoniae (PNSP) were first detected in the 1960s, and are now common worldwide, predominantly through the international spread of a limited number of strains. Extant PNSP are characterized by mosaic pbp2x, pbp2b and pbp1a genes generated by interspecies recombinations, with the extent of these alterations determining the range and concentrations of ß-lactams to which the genotype is non-susceptible. The complexity of the genetics underlying these phenotypes has been the subject of both molecular microbiology and genome-wide association and epistasis analyses. Such studies can aid our understanding of PNSP evolution and help improve the already highly-performing bioinformatic methods capable of identifying PNSP from genomic surveillance data.