Non-pharmaceutical interventions for COVID-19 reduced the incidence of infectious diseases: a controlled interrupted time-series study.

BACKGROUND: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to suppress the spread of coronavirus disease 2019 (COVID-19). However, few studies have evaluated the effect of NPIs on other infectious diseases and none has assessed the avoided disease burden associated with NPIs. We aimed to assess the effect of NPIs on the incidence of infectious diseases during the COVID-19 pandemic in 2020 and evaluate the health economic benefits related to the reduction in the incidence of infectious diseases. METHODS: Data on 10 notifiable infectious diseases across China during 2010-2020 were extracted from the China Information System for Disease Control and Prevention. A two-stage controlled interrupted time-series design with a quasi-Poisson regression model was used to examine the impact of NPIs on the incidence of infectious diseases. The analysis was first performed at the provincial-level administrative divisions (PLADs) level in China, then the PLAD-specific estimates were pooled using a random-effect meta-analysis. RESULTS: A total of 61,393,737 cases of 10 infectious diseases were identified. The implementation of NPIs was associated with 5.13 million (95% confidence interval [CI] 3.45‒7.42) avoided cases and USD 1.77 billion (95% CI 1.18‒2.57) avoided hospital expenditures in 2020. There were 4.52 million (95% CI 3.00‒6.63) avoided cases for children and adolescents, corresponding to 88.2% of total avoided cases. The top leading cause of avoided burden attributable to NPIs was influenza [avoided percentage (AP): 89.3%; 95% CI 84.5‒92.6]. Socioeconomic status and population density were effect modifiers. CONCLUSIONS: NPIs for COVID-19 could effectively control the prevalence of infectious diseases, with patterns of risk varying by socioeconomic status. These findings have important implications for informing targeted strategies to prevent infectious diseases.

The association between air pollutants, meteorological factors and tuberculosis cases in Beijing, China: A seven-year time series study.

BACKGROUND: Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing. OBJECTIVE: The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB. METHODS: Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM10, PM2.5, SO2, NO2, CO and O3, were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing. RESULTS: In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 µg/m3 increase in NO2 in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 µg/m3 increase in O3 in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO2, O3, average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM2.5, SO2, sunshine duration and TB cases. CONCLUSION: Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.

[Risk factors for influenza A (H1N1)-associated pneumonia on hospitalized people less than 18 years old in China, 2009-2010].

OBJECTIVE: To describe the epidemiological and clinical features of hospitalized people less than 18 years old with influenza A (H1N1)-associated pneumonia and associated risk factors. METHODS: Through Chinese Reporting System of Influenza A (H1N1), children aged under 18 years who were hospitalized with laboratory confirmed influenza A (H1N1), case report forms and related information on pneumonia were collected between 1 September 2009 and 4 July 2010. Epidemiological and clinical characteristics including demographics, underlying chronic diseases, treatment, complications and clinical outcome etc. were described. Hospitalized children with pneumonia were compared with those without the above mentioned features, through the univariate and multivariate analysis. RESULTS: There were 4240 influenza A (H1N1)-associated hospitalized children with case report forms identified. Of the 4107 influenza A (H1N1)-associated hospitalized children with related information on pneumonia shown in the case report forms, 2289 (55.7%) of them had pneumonia. Hospitalized children with influenza A (H1N1)-associated pneumonia had a younger median age (4.9 year old), when compared with those without pneumonia (13.1 year old, P<0.0001). When compared with the hospitalized children without pneumonia, those hospitalized children with pneumonia were more likely to require intensive care unit care, using mechanical ventilation equipment to develop ARDS, respiratory failure or leading to death. Data from multivariate analysis showed that children aged<6 months (OR=7.08, 95%CI: 4.15-12.06) between 6 and 23 months (aOR=8.26, 95%CI: 6.10-11.20) or between 2 to 4 year old (aOR=9.53, 95%CI: 7.39-12.29) were more likely to develop pneumonia than children aged 5 to 17. Factors as having asthma (OR=12.19, 95%CI: 5.18-28.72), cardiovascular disease (OR=5.19, 95%CI: 1.94-13.90), chronic renal diseases (OR=2.14, 95%CI: 1.02-4.53), chronic hepatic diseases (OR=5.26, 95%CI: 1.40-19.81) and allergy (OR=2.54, 95%CI: 1.64-3.93) were significantly associated with influenza A (H1N1)-associated pneumonia. Risk of complication with pneumonia had an increase when oseltamivir treatment was initiated>2 days after the onset of illness. CONCLUSION: Pneumonia was a common complication among children hospitalized with influenza A (H1N1). Hospitalized children with influenza A (H1N1)-associated pneumonia were more likely to develop either severe clinical courses or outcomes than those without pneumonia.

[Epidemiological characteristics on the clustering nature of pandemic (H1N1) 2009 in China].

OBJECTIVE: To study the epidemiological characteristics on the clustering nature of pandemic (H1N1) 2009 in China. METHODS: Time and place distribution of pandemic (H1N1) 2009 on the nature of clustering through data from Public Health Emergency Management Information System were described. RESULTS: As of August 10, 2010, 2773 pandemic (H1N1) 2009 clusters, a total of 77 363 cases (including 20 deaths) were reported in the mainland of China. The most reported number of clusters was from schools and kindergartens with the total number of 2498 (accounted for 90.08% of the total number). Middle schools appeared the have the most clusters (1223, accounting for 48.96%). The number of clusters reported in the southern provinces (cities) accounted for 77.03% of the total, and was more than that in the northern provinces (cities). Two reported peaks in the southern provinces (cities) were in June and November, 2009, respectively. There was only one reported peak in the northern provinces in September, 2009. CONCLUSION: Time and place distribution characteristics on the clusters of pandemic (H1N1) 2009 were similar to the seasonal influenza, but the beginning of winter peak was much earlier and intensity of reporting was much higher on the clusters of pandemic (H1N1) 2009 than that of seasonal influenza.

Indications that live poultry markets are a major source of human H5N1 influenza virus infection in China.

Human infections of H5N1 highly pathogenic avian influenza virus have continued to occur in China without corresponding outbreaks in poultry, and there is little conclusive evidence of the source of these infections. Seeking to identify the source of the human infections, we sequenced 31 H5N1 viruses isolated from humans in China (2005 to 2010). We found a number of viral genotypes, not all of which have similar known avian virus counterparts. Guided by patient questionnaire data, we also obtained environmental samples from live poultry markets and dwellings frequented by six individuals prior to disease onset (2008 and 2009). H5N1 viruses were isolated from 4 of the 6 live poultry markets sampled. In each case, the genetic sequences of the environmental and corresponding human isolates were highly similar, demonstrating a link between human infection and live poultry markets. Therefore, infection control measures in live poultry markets are likely to reduce human H5N1 infection in China.

Climate variability and hemorrhagic fever with renal syndrome transmission in Northeastern China.

BACKGROUND: The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by climatic variables. However, few studies have examined the quantitative relationship between climate variation and HFRS transmission. OBJECTIVE: We examined the potential impact of climate variability on HFRS transmission and developed climate-based forecasting models for HFRS in northeastern China. METHODS: We obtained data on monthly counts of reported HFRS cases in Elunchun and Molidawahaner counties for 1997-2007 from the Inner Mongolia Center for Disease Control and Prevention and climate data from the Chinese Bureau of Meteorology. Cross-correlations assessed crude associations between climate variables, including rainfall, land surface temperature (LST), relative humidity (RH), and the multivariate El Niño Southern Oscillation (ENSO) index (MEI) and monthly HFRS cases over a range of lags. We used time-series Poisson regression models to examine the independent contribution of climatic variables to HFRS transmission. RESULTS: Cross-correlation analyses showed that rainfall, LST, RH, and MEI were significantly associated with monthly HFRS cases with lags of 3-5 months in both study areas. The results of Poisson regression indicated that after controlling for the autocorrelation, seasonality, and long-term trend, rainfall, LST, RH, and MEI with lags of 3-5 months were associated with HFRS in both study areas. The final model had good accuracy in forecasting the occurrence of HFRS. CONCLUSIONS: Climate variability plays a significant role in HFRS transmission in northeastern China. The model developed in this study has implications for HFRS control and prevention.