OBJECTIVES: Although the role of specific holidays in modifying transmission dynamics of infectious diseases has received some research attention, the epidemiological impact of public holidays on the transmission of coronavirus disease 2019 (COVID-19) remains unclear. METHODS: To assess the extent of increased transmission frequency during public holidays, we collected COVID-19 incidence and mobility data in Hokkaido, Tokyo, Aichi, and Osaka from February 15, 2020 to September 30, 2021. Models linking the estimated effective reproduction number (Rt) with raw or adjusted mobility, public holidays, and the state of emergency declaration were developed. The best-fit model included public holidays as an essential input variable, and was used to calculate counterfactuals of Rt in the absence of holidays. RESULTS: During public holidays, on average, Rt increased by 5.71%, 3.19%, 4.84%, and 24.82% in Hokkaido, Tokyo, Aichi, and Osaka, respectively, resulting in a total increase of 580 (95% confidence interval [CI], 213 to 954), 2,209 (95% CI, 1,230 to 3,201), 1,086 (95% CI, 478 to 1,686), and 5,211 (95% CI, 4,554 to 5,867) cases that were attributable to the impact of public holidays. CONCLUSIONS Public holidays intensified the transmission of COVID-19, highlighting the importance of considering public holidays in designing appropriate public health and social measures in the future.

BACKGROUNDRRM1 may be a prognostic factor in non-small cell lung cancer (NSCLC). The aim of this study is to evaluate RRM1 expression and prognosis in NSCLC by the means of tissue microarray.

METHODSA total of 417 paraffin-embedded specimens of NSCLC from Lung Cancer Study Center in Guangdong Provincial People's Hospital were collected and tissue microarray was constructed. RRM1 expression was detected by SP method and its correlation with prognosis was evaluated.

RESULTSNo statistic difference was found in RRM1 expression in different gender, age, tumor site, histology, differentiation, T stage, N stage, M stage and pTNM stage groups (P > 0.05). Univariate analysis showed that RRM1 was not an independent prognostic factor (P > 0.05). At the multivariate analysis, differentiation and N stage were considered independent prognostic factors.

CONCLUSIONSRRM1 expression detected by immunohistology is not an independent prognostic factor in NSCLC. TNM stage is still the best prognostic factor up to now.

ObjectiveTo investigate the characteristics of gender difference and the trend of the mortality rate of senile dementia in registered population in Shanghai from year 2002 to 2018， and to provide the basis for formulating relative intervention measures before and after senile dementia from an public-health view. MethodsBased on the collected data of death registration， focused on the senile dementia disease codes F03，G30.0，G30.1，G30.8，G30.9 according to The International Classification of Diseases 10th revision （ICD-10）. We analyzed the characteristics of gender difference in the mortality rate of senile dementia in registered population in Shanghai from year 2002 to 2018. According to ASR， we calculated the standardized mortality rate of senile dementia， and used the chi-square test to compare the difference between the gender mortality rates. The trend and the turning point of the mortality rate of senile dementia were determined by linear regression analysis by Join-point. ResultsThe crude mortality rate of senile dementia in the registered population in Shanghai from year 2002 to 2018 was 5.46/10⁵， 3.50/10⁵ in males and 7.43/10⁵ in females. The standardized mortality rate of senile dementia was 2.61/10⁵， 1.67/10⁵ in males and 3.56/10⁵ in females. The trend of the standardized mortality rate of senile dementia in 17 years decreased ［APC=-5.5（-6.5，-4.5）%，P<0.01］. The trend of the standardized mortality rate of senile dementia decreased in both males ［APC=-4.9（-6.2，-3.6）%，P<0.01］ and females ［APC=-5.9（-6.9，-4.9）%，P<0.01］. The trend of the gender difference decreased ［APC=-6.8（-8.2，-5.3）%，P<0.01］. The mortality rate of senile dementia was higher in females than in males ［（χ²=33.63，P<0.01）］. ConclusionThe mortality rate of senile dementia in females is higher than in males in Shanghai， though the trend of the gender difference decreased. This gender difference is worth of attention.

ObjectiveTo analyze the dynamic response relationship between urban development and mortality rate in Shanghai， and to predict the trend of mortality rate changes. MethodsBy analyzing the total mortality rate （TMR）， gross domestic product （GDP） and socio-demographic index （SDI） in Shanghai from 1978 to 2017， a vector autoregressive （VAR） model was constructed to evaluate the impact of urban development on the mortality rate. ResultsThe fitted R2 of the VAR model was 0.92. The short-term effect of GDP on the improvement of death level was negative， while the long-term effect was positive， and the SDI was negative regardless of the short-term and long-term effects. By the tenth year， GDP and SDI contributed 10.61% and 27.25% to TMR changes， respectively. The model predicted that the mortality rate in Shanghai would be 9.17 per thousand by 2030. ConclusionLong-term economic growth can effectively promote a decline in population mortality. However， as the economy develops vigorously， the adverse effects of declining birth rates and population aging on population health during the era of high-level population development should not be ignored.