Italy was the rst, among all the European countries, to be strongly hit by the Covid-19 pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). The virus, proven to be very contagious, infected more than 9 million people worldwide (in June 2020). Nevertheless, it is not clear the role of air pollution and meteorological conditions on virus transmission. In this study, we quantitatively assessed how the meteorological and air quality parameters are correlated to the Covid-19 transmission in Lombardy (Northern Italy), the region epicenter of the virus outbreak. Our main ndings highlight that temperature and humidity related variables are negatively correlated to the virus transmission, whereas air pollution (PM 2.5) shows a positive correlation. In other words, Covid-19 pandemic transmission prefers dry and cool environmental conditions, as well as polluted air. For these reasons, the virus might easier spread in un ltered air-conditioned environments. Those results will be supporting decision makers to contain new possible outbreaks.

No abstract

The coronavirus (COVID-19) epidemic reported for the first time in Wuhan, China at the end of 2019, which has caused 4648 deaths in China as of July 10, 2020. This study explored the temporal correlation between the case fatality rate (CFR) of COVID-19 and particulate matter (PM) in Wuhan. We conducted a time series analysis to examine the temporal day-by-day associations. We observed a higher CFR of COVID-19 with increasing concentrations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 μm or less (PM 10 ) and fine PM with an aerodynamic diameter of 2.5 μm or less (PM 2.5 ) in the temporal scale. This association may affect patients with mild to severe disease progression and affect their prognosis.

Purpose To examine the association between meteorological factors (temperature, relative humidity, wind speed, and UV radiation) and transmission capacity of COVID-19. Methods We collected daily numbers of COVID-19 cases in 202 locations in 8 countries. We matched meteorological data from the NOAA National Centers for Environmental Information. We used a time-frequency approach to examine the possible association between meteorological conditions and basic reproductive number (R 0 ) of COVID-19. We determined the correlations between meteorological factors and R 0 of COVID-19 using multiple linear regression models and meta-analysis. We further validated our results using a susceptible-exposed-infectious-recovered (SEIR) metapopulation model to simulate the changes of daily cases of COVID-19 in China under different temperatures and relative humidity conditions. Principal results Temperature did not exhibit significant association with R 0 of COVID-19 (meta p = 0.446). Also, relative humidity (meta p = 0.215), wind speed (meta p = 0.986), and ultraviolet (UV) radiation (meta p = 0.491) were not significantly associated with R 0 either. The SEIR model in China showed that with a wide range of meteorological conditions, the number of COVID-19 confirmed cases would not change substantially. Conclusions Meteorological conditions did not have statistically significant associations with the R 0 of COVID-19. Warmer weather alone seems unlikely to reduce the COVID-19 transmission.

This study aims to explore the relationship between ambient NO 2 levels and the transmission ability (basic reproductive number, R 0 ) of COVID-19 in 63 Chinese cities. After adjustment for temperature and relative humidity, R 0 was positively associated with NO 2 concentration at city level. The temporal analysis within Hubei province indicated that all the 11 Hubei cities (except Xianning City) had significant positive correlations between NO 2 concentration (with 12-day time lag) and R 0 (r > 0.51, p < 0.005). Since the association between ambient NO 2 and R 0 indicated NO 2 may increase underlying risk of infection in the transmission process of COVID-19. In addition, NO 2 is also an indicator of traffic-related air pollution, the association between NO 2 and COVID-19′s spreadability suggest that reduced population movement may have reduced the spread of the SARS-CoV-2.

none

To evaluate the achievements of China's immunization program between 1950 and 2018, we chose 11 vaccine-preventable diseases (VPDs) as representative notifiable diseases and used annual surveillance data obtained between 1950 and 2018 to derive disease incidence and mortality trends. Quasi-Poisson and polynomial regression models were used to estimate the impacts of specific vaccine programs, and life-table methods were used to calculate the loss of life expectancy, years of life lost, and loss of working years. The total notification number for the 11 VPDs was 211,866,000 from 1950 to 2018. The greatest number occurred in 1959, with a total incidence of 1,723 per million persons. From 1978 to 2018, a substantial decline was observed in the incidence of major infectious diseases. The incidence of pertussis fell 98% from 126.35 to 1.58 per million, and the incidences of measles, meningococcal meningitis, and Japanese encephalitis fell 99%, 99%, and 98%, respectively. The regression models showed that most of the 11 diseases exhibited dramatic declines in morbidity after their integration into the Expanded Program on Immunization (EPI), while varicella and paratyphoid fever, which were not integrated into the EPI, showed increased morbidity. From 1978 to 2018, the total life expectancy for the 11 VPDs increased by 0.79 years, and similar results were obtained for different age groups. China has had great success in controlling VPDs in recent decades, and improving vaccination coverage is a key aspect of controlling VPDs in China.

Background Elimination of hepatitis B virus (HBV) is a striking challenge for countries with high or moderate disease burden. Therefore, using China as a practical case to share experiences for similar countries may accelerate the achievement of the WHO 2030 target of 90% reduction in HBV-related incidence. We aim to evaluate the impact of national HBV immunization strategies in China; and the feasibility to achieve WHO 2030 targets under different scenarios. Methods We constructed an expanded Susceptible-Exposed-Infectious-Recovered (SEIR) model and decision tree-Markov model to estimate the epidemic of HBV in China, assess the feasibility of 2030 Elimination Goals through the projections and conduct the economic analysis. Least square method was used to calibrate the expanded SEIR model by yearly data of laboratory-confirmed HBV cases from 1990 to 2018. Two models were separately used to evaluate the impact and cost-effectiveness of HBV vaccine by comparing prevalence of chronic HBV infections, quality-adjusted life-years (QALYs), incremental cost effectiveness ratio and benefit–cost ratio (BCR) under various intervention options, providing a basis for exploring new containment strategies. Results Between 1990 and 2020, the number of chronic HBV infections decreased by 33.9%. The current status quo would lead to 55.73 million infections (3.95% prevalence) in 2030, compared to 90.63 million (6.42% prevalence) of the “Without the NIP” scenario (NIP: National Immunization Program), 114.78 million (8.13% prevalence) without any interventions. The prevention of mother to child transmission (PMTCT) strategy showed a net benefit as 12,283.50 dollars per person, with BCR as 12.66, which is higher than that of universal vaccination at 9.49. Compared with no screening and no vaccination, the PMTCT strategy could save 7726.03 dollars for each QALY increase. Conclusions Our findings proved the HBV vaccination has demonstrated a substantial positive impact on controlling the epidemic of HBV in terms of effectiveness and economy after about 30 years of implementation of the national hepatitis B immunization program which also provided containment experience for high or medium burden countries. As for China, the next step should focus on exploring strategies to improve diagnosis and treatment coverage to reduce the burden of HBV-related deaths and ultimately eliminate HBV.