Association between inequalities in human resources for health and all cause and cause specific mortality in 172 countries and territories, 1990-2019: observational study.

OBJECTIVE: To explore inequalities in human resources for health (HRH) in relation to all cause and cause specific mortality globally in 1990-2019. DESIGN: Observational study. SETTING: 172 countries and territories. DATA SOURCES: Databases of the Global Burden of Disease Study 2019, United Nations Statistics, and Our World in Data. MAIN OUTCOME MEASURES: The main outcome was age standardized all cause mortality per 100 000 population in relation to HRH density per 10 000 population, and secondary outcome was age standardized cause specific mortality. The Lorenz curve and the concentration index (CCI) were used to assess trends and inequalities in HRH. RESULTS: Globally, the total HRH density per 10 000 population increased, from 56.0 in 1990 to 142.5 in 2019, whereas age standardized all cause mortality per 100 000 population decreased, from 995.5 in 1990 to 743.8 in 2019. The Lorenz curve lay below the equality line and CCI was 0.43 (P<0.05), indicating that the health workforce was more concentrated among countries and territories ranked high on the human development index. The CCI for HRH was stable, at about 0.42-0.43 between 1990 and 2001 and continued to decline (narrowed inequality), from 0.43 in 2001 to 0.38 in 2019 (P<0.001). In the multivariable generalized estimating equation model, a negative association was found between total HRH level and all cause mortality, with the highest levels of HRH as reference (low: incidence risk ratio 1.15, 95% confidence interval 1.00 to 1.32; middle: 1.14, 1.01 to 1.29; high: 1.18, 1.08 to 1.28). A negative association between total HRH density and mortality rate was more pronounced for some types of cause specific mortality, including neglected tropical diseases and malaria, enteric infections, maternal and neonatal disorders, and diabetes and kidney diseases. The risk of death was more likely to be higher in people from countries and territories with a lower density of doctors, dentistry staff, pharmaceutical staff, aides and emergency medical workers, optometrists, psychologists, personal care workers, physiotherapists, and radiographers. CONCLUSIONS: Inequalities in HRH have been decreasing over the past 30 years globally but persist. All cause mortality and most types of cause specific mortality were relatively higher in countries and territories with a limited health workforce, especially for several specific HRH types among priority diseases. The findings highlight the importance of strengthening political commitment to develop equity oriented health workforce policies, expanding health financing, and implementing targeted measures to reduce deaths related to inadequate HRH to achieve universal health coverage by 2030.

Trends of SARS-CoV-2 Infection Among Couriers in Risky Business After the Optimization of Prevention and Control Measures - China, December 2022 to January 2023.

Introduction: On December 7, 2022, China implemented "Ten New Measures" to optimize prevention and control measures for coronavirus disease 2019 (COVID-19). The purpose of this study was to evaluate the national and regional trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among couriers in China from December 2022 to January 2023. Methods: Data from the National Sentinel Community-based Surveillance in China was utilized, including participants from 31 provincial-level administrative divisions and Xinjiang Production and Construction Corps. Participants were tested for SARS-CoV-2 infection twice a week from December 16, 2022 to January 12, 2023. Infection was defined as a positive result for SARS-CoV-2 nucleic acid or antigen. The daily average newly positive rate of SARS-CoV-2 infection and the estimated daily percentage change (EDPC) were calculated. Results: In this cohort, 8 rounds of data were collected. The daily average newly positive rate of SARS-CoV-2 infection decreased from 4.99% in Round 1 to 0.41% in Round 8, with an EDPC of -33.0%. Similar trends of the positive rate were also observed in the eastern (EDPC: -27.7%), central (EDPC: -38.0%) and western regions (EDPC: -25.5%). Couriers and community population showed a similar temporal trend, with the peak daily average newly positive rate of couriers being higher than that of community population. After Round 2, the daily average newly positive rate of couriers decreased sharply, becoming lower than that of community population in the same period. Conclusions: The peak of SARS-CoV-2 infection among couriers in China has passed. As couriers are a key population for SARS-CoV-2 infection, they should be monitored continuously.

Long-term impact of the COVID-19 pandemic on health services utilization in China: A nationwide longitudinal study.

Background: Long-term impact of the COVID-19 pandemic on health services utilization is unknown. We aim to assess the long-term effect of the COVID-19 pandemic on health services utilization in China. Methods: Between Jan 2017 and Dec 2021, we conducted a nationwide longitudinal study using routinely collected data on health services utilization in the National Health Information System of China. We extracted national and provincial data of demographic characteristics, socio-economic characteristics, and health resources. Interrupted time-series segmented negative binominal regression models were used. Results: A total of 34.2 billion health facilities visits and 1.1 billion inpatients discharged were included. The largest negative impact of COVID-19 pandemic on the health services utilization was during containment period, that health facility visits were observed 32% reduction in hospitals (adjusted incidence risk ratios [aRRs] 0.68, 95%CI: 0.50-0.92), 27% reduction in community health centers (aRR 0.73, 95%CI: 0.57-0.93), and 22% reduction township centers (aRR 0.78, 95%CI: 0.67-0.91), respectively. The impact on health facility visits and inpatients discharged were reduced and eliminated over time (all p>0.05). However, the negative impact on utilization rate of beds, average length of stay, average inpatient costs, and average outpatient costs in different level of health facilities still existed two years later (all p<0.05). Conclusions: The impact of the COVID-19 pandemic on health services utilization was largest during containment period and reduced over time, but it still existed two years later. There are disparities in the recovery of health services. Our findings highlighted the importance of maintaining primary healthcare services during the pandemic and strengthen resilient health system on the rapid recovery of medical services.

Trends of SARS-CoV-2 Infection in Sentinel Community-Based Surveillance After the Optimization of Prevention and Control Measures - China, December 2022-January 2023.

Introduction: On December 7, 2022, China implemented the "Ten New Measures" to optimize its prevention and control measures for coronavirus disease 2019 (COVID-19). To provide the latest data after the optimization, we evaluated trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among the community population in China. Methods: We utilized data from the National Sentinel Community-Based Surveillance (NSCS) system in China to assess trends of SARS-CoV-2 infection. NSCS is a national community-based surveillance cohort with 0.42 million participants from all 31 provincial-level administrative divisions (PLADs) and Xinjiang Production and Construction Corps (XPCC). Participants were tested for infection twice a week (a total of eight rounds) from December 16, 2022 to January 12, 2023. SARS-CoV-2 infection was defined as testing positive for SARS-CoV-2 nucleic acid or antigen. We calculated the daily average of newly positive rates of SARS-CoV-2 infection. Results: In this national cohort, the daily average newly positive rate of SARS-CoV-2 infection decreased from 4.13% in Round 1 (December 16-19, 2022) to 0.69% in Round 8 (January 10-12, 2023). The epidemic peak occurred in Round 2 (December 20-22, 2022). Similar trends were observed in urban areas (decreasing from 4.65% to 0.73%), rural areas (decreasing from 2.83% to 0.57%), the eastern region (decreasing from 4.18% to 0.67%), the central region (decreasing from 5.43% to 0.61%), and the western region (decreasing from 3.01% to 0.77%). Conclusions: NSCS data showed that the peak of SARS-CoV-2 infection in China had passed. SARS-CoV-2 infection in community populations in China is currently at a low epidemic level.

Trends of SARS-CoV-2 Infection in Rural Area in Sentinel Community-Based Surveillance - China, December 2022 to January 2023.

Introduction: In late 2022, a rapid transmission of Omicron variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred throughout China. The purpose of this study was to provide the latest data and evaluate trends of SARS-CoV-2 infection in rural China among the community population. Methods: Data on SARS-CoV-2 infection among approximately 90,000 participants in rural China were collected by the National Sentinel Community-Based Surveillance (NSCS) system. Participants were tested for SARS-CoV-2 infection (defined as positive for SARS-CoV-2 nucleic acid or antigen) twice weekly from December 16, 2022 to January 12, 2023. The daily average of newly positive rate and its estimated daily percentage change were calculated to describe the national and regional trends of SARS-CoV-2 infection in rural China. Results: In rural China, the daily average new positive rate of SARS-CoV-2 infection peaked at 4.79% between December 20-22, 2022 and then decreased to 0.57% between January 10-12, 2023, with an average decrease of 29.95% per round. The peak of new SARS-CoV-2 infection was slightly earlier and lower in North China (5.28% between December 20-22, 2022) than in South China (5.63% between December 23-26, 2022), and then converged from December 30, 2022 to January 2, 2023. The peak of 6.09% occurred between December 20-22, 2022 in eastern China, while the peak of 5.99% occurred later, between December 27-29, 2022, in central China. Conclusions: Overall, the epidemic wave in rural China peaked between December 20-22, 2022, and passed quickly following the optimization of prevention and control measures. Currently, SARS-CoV-2 infection in community populations in rural China is sporadic.

Assessing acceptability of the fourth dose against COVID-19 among Chinese adults: A population-based survey.

Coronavirus disease 2019 (COVID-19) has wreaked havoc across the globe for approximately three years. Vaccination is a key factor to ending this pandemic, but its protective effect diminishes over time. A second booster dose at the right time is needed. To explore the willingness to receive the fourth dose of the COVID-19 vaccine and its influencing factors, we commenced a national, cross-sectional and anonymous survey in mainland China among people aged 18 and above from October 24 to November 7, 2022. A total of 3,224 respondents were eventually included. The acceptance rate of the fourth dose was 81.1% (95% CI: 79.8-82.5%), while it was 72.6% (95% CI: 71.1-74.2%) for a heterologous booster. Confidence in current domestic situation and the effectiveness of previous vaccinations, and uncertainty about extra protection were the main reasons for vaccine hesitancy. Perceived benefit (aOR = 1.29, 95% CI: 1.159-1.40) and cues to action (aOR = 1.73, 95% CI: 1.60-1.88) were positively associated with the vaccine acceptance, whereas perceived barriers (aOR = 0.78, 95% CI: 0.72-0.84) and self-efficacy (aOR = 0.79, 95% CI: 0.71-0.89) were both negatively associated with it. Additionally, sex, age, COVID-19 vaccination history, time for social media, and satisfaction with the government's response to COVID-19 were also factors affecting vaccination intention. Factors influencing the intention of heterologous booster were similar to the above results. It is of profound theoretical and practical significance to clarify the population's willingness to vaccinate in advance and explore the relevant influencing factors for the subsequent development and promotion of the fourth-dose vaccination strategies.

Trends and disparities in 44 national notifiable infectious diseases in China: an analysis of national surveillance data from 2010 to 2019.

BACKGROUND: Research assessing the changing epidemiology of infectious diseases in China after the implementation of new health-care reform in 2009 was scarce. We aimed to get the latest trends and disparities of national notifiable infectious diseases by age, sex, province and seasons in China from 2010 to 2019. METHODS: The number of incident cases and deaths, incidence rate and mortality of 44 national notifiable infectious diseases by sex, age groups, and provincial regions from 2010 to 2019 was extracted from the China Information System for Disease Control and Prevention and official reports, and divided into six kinds of infectious diseases by transmission routes and three classes (A, B and C) in this descriptive study. Estimated annual percentage changes (EAPCs) were calculated to quantify the temporal trends of incidence and mortality rate. We calculated concentration index to measure economic-related inequality. Segmented interrupted time-series analysis was used to estimate the impact of the COVID-19 pandemic on the epidemic of notifiable infectious disease. RESULTS: The trend of incidence rate on six kinds of infectious diseases by transmission routes was stable, while only mortality of sexual, blood-borne, and mother-to-child-borne infectious diseases increased from 0.6466 per 100 000 population in 2010 to 1.5499 per 100 000 population in 2019 by 8.76% per year (95%CI: 6.88-10.68). There was a decreasing trend of incidence rate on Class-A infectious diseases (EAPC=-16.30%; 95%CI: -27.93 - -2.79) and Class-B infectious diseases (EAPC=-1.05%; 95%CI: -1.56 - -0.54), while an increasing trend on Class-C infectious diseases (EAPC=6.22%; 95%CI: 2.13~10.48). For mortality, there was a decreasing trend on Class-C infectious diseases (EAPC=-14.76%; 95%CI: -23.46 - -5.07), and an increasing trend on Class-B infectious diseases (EAPC=4.56%; 95%CI: 2.44-6.72). In 2019, the infectious diseases with highest incidence rate and mortality were respiratory diseases (340.95 per 100 000 population), and sexual, blood-borne, and mother-to-child-borne infectious diseases (1.5459 per 100 000 population), respectively. The greatest increasing trend of incidence rate was observed in seasonal influenza, from 4.83 per 100 000 population in 2010 to 253.36 per 100 000 population in 2019 by 45.16% per year (95%CI: 29.81-62.33), especially among female and children aged 0 - 4 years old. The top disease with highest mortality was still AIDs which had the highest average yearly mortality in 24 provinces from 2010 to 2019, and its incidence rate (EAPC=14.99%; 95%CI: 8.75-21.59) and mortality (EAPC=9.65; 95%CI: 7.71-11.63) both increased from 2010 to 2019, especially among people aged 44 - 59 years old and 60 or older. Male incidence rate and mortality were higher than females each year from 2010 to 2018 on 29 and 10 infectious diseases, respectively. Additionally, sex differences of incidence and mortality of AIDS were becoming larger. The curve lay above the equality line, with the negative value of the concentration index, which indicated that economic-related health disparities exist in the distribution of incidence rate and mortality of respiratory diseases (incidence rate: the concentration index = -0.063, P<0.0001; mortality: the concentration index = -0.131, P<0.001), sexual, blood-borne, and mother-to-child-borne infectious diseases (incidence rate: the concentration index = -0.039, P=0.0192; mortality: the concentration index = -0.207, P<0.0001), and the inequality disadvantageous to the poor (pro-rich). Respiratory diseases (Dec, Jan), intestinal diseases (May, Jun, July), zoonotic infectious diseases (Mar-Jul) and vector-borne infectious diseases (Sep-Oct) had distinct seasonal epidemic patterns. In addition, segmented interrupted time-series analyses showed that, after adjusted for potential seasonality, autocorrelation, GDP per capita, number of primary medical institutions and other factors, there was no significant impact of COVID-19 epidemic on the monthly incidence rate of six kinds of infectious diseases by transmission routes from 2018 to 2020 (all P>0.05). CONCLUSIONS: The incidence rates of six kinds of infectious diseases were stable in the past decade, and incidence rates of Class-A and Class-B infectious diseases were deceasing, because of comprehensive prevention and control measures and strengthened health system after the implementation of the new health-care reform in China since 2009. However, age, gender, regional and economic disparities were still observed. Concerted efforts are needed to reduce the impact of seasonal influenza (especially among children aged 0 - 4 years old) and the mortality of AIDs (especially among people aged 44 - 59 years old and 60 or older). More attention should be paid to the disparities on the burden of infectious diseases. This article is protected by copyright. All rights reserved.

Millions of excess cases and thousands of excess deaths of malaria occurred globally in 2020 during the COVID-19 pandemic.

Background: The COVID-19 pandemic disrupted malaria-related health care services, leading to an excess burden of malaria. However, there is a lack of research on the indirect global impact of the COVID-19 pandemic on malaria. We aimed to assess the excess burden of malaria due to the COVID-19 pandemic in malaria-endemic countries in 2020. Methods: Based on data from the World Health Organization Global Observatory, we used estimated annual percentage changes (EAPCs) from 2000 to 2019 (model A) and from 2015 to 2019 (model B) to predict the malaria burden in 2020. We calculated the ratios between reported and predicted malaria incidence (incidence rate ratio (IRR)) and mortality rates (mortality rate ratio (MRR)). Results: In 2020, African countries suffered the most from malaria, with the largest number of malaria cases (64.7 million) and deaths (151 thousand) observed in Nigeria. Most countries showed a decrease in malaria incidence and mortality rates from 2000 to 2019, with the strongest decline in incidence rates in Bhutan (EAPC = -35.7%, 95% CI = -38.7 to -32.5%) and mortality rates Ecuador (EAPC = -40.6%, 95% confidence interval (CI) = -46.6 to -33.8%). During the COVID-19 pandemic in 2020, there was a total of 18 million excess malaria cases and 83 291 excess deaths per model A, and 7.4 million excess cases and 33 528 excess deaths per model B globally. Malaria incidence rates increased excessively in over 50% of the malaria-endemic countries, with the greatest increase in Costa Rica (IRR = 35.6) per model A and Bhutan (IRR = 15.6) per model B. Mortality rates had increased excessively in around 70% of the malaria-endemic countries, with the greatest increase in Ecuador in both model A (MRR = 580) and model B (MRR = 58). Conclusions: The emergence of the COVID-19 pandemic indirectly caused an increase in the prevalence of malaria and thwarted progress in malaria control. Global efforts to control the pandemic's impact should be balanced with malaria control to ensure that the goal for global malaria elimination is achieved on time.

Acceptance of the COVID-19 vaccine booster dose and associated factors among the elderly in China based on the health belief model (HBM): A national cross-sectional study.

Background: The reluctance of individuals to obtain solid vaccine-induced immunity represents a fundamental challenge to containing the spread of SARS-CoV-2, including its highly mutated variants. We aimed to assess vaccination acceptance and associated factors for the COVID-19 vaccine booster dose among elderly people (≥60 years old) in China, providing a theoretical and practical reference for universal vaccination policy. Methods: A national anonymous survey was conducted in mainland China from May 25 to June 8, 2022, using a stratified random sampling method. Individuals 60 years of age and above were the target population. A chi-squared test and Cochran-Armitage test for trend were used to compare and examine vaccine acceptance rates by characteristics. Via a backward stepwise method, multivariable logistic regression models were established to assess factors associated with booster dose acceptance. Two-sided P < 0.05 was considered statistically significant. Results: Of 3,321 eligible participants, 82.8% (95% CI: 81.5-84.1%) were willing to receive COVID-19 vaccine booster shots. Concerns about contraindications (38.3%), vaccine safety (32.0%), and limited movement (28.0%) were the main reasons for vaccine hesitancy. Nearly one-third still believed that the booster dose was unnecessary after receiving the initial vaccination. Older adults with a low level of perceived barriers (aOR = 1.86, 95% CI, 1.03-3.38), a high level of perceived benefit (aOR = 2.31, 95% CI, 1.38-3.87), and higher cues to action (moderate, aOR = 2.22, 95% CI, 1.39-3.56; high, aOR = 5.46, 95% CI: 3.44-8.67) were more likely to accept the booster dose. Other major factors affecting the booster dose acceptance rate were occupation, time spent on social media, vaccination history, and a high knowledge score for COVID-19 and vaccines. In addition, for those over 70 years of age, rising awareness of susceptibility could be a better gateway for improving their willingness to get vaccinated. Conclusions: A total of 82.8% of recruited older adults were willing to receive the booster dose. Acceptance behaviors were closely related to occupation, time spent on social media, vaccination history, knowledge factors, perception of barriers, and benefit, as well as action cues. Targeted public health measures are a priority for improving the vaccination coverage of valid immunity among the elderly population, not only to prevent infection and poor prognosis caused by emerging variants but also to reduce the huge disease and economic burden caused by the long-term sequelae after SARS-CoV-2 infection.

Neighborhood social cohesion is associated with the willingness toward the booster dose of COVID-19 vaccines among the Chinese older population.

Neighborhood social cohesion is a prominent psychosocial factor during the pandemic, and trust in neighbors is critical for implementing health prevention-related behaviors with public health messages. We planned to specifically explore the association between neighborhood social cohesion and vaccine acceptability among older adults (≥60 years) in China. Using a random stratified sampling method, an anonymous cross-sectional online survey was conducted in mainland China via a professional scientific data platform from May 25 to June 8, 2022. A revised Social Cohesion Scale was applied to evaluate the level of neighborhood social cohesion. Of the 3,321 recruited respondents aged 60 and above, 82.8% (95% CI: 81.5-84.1) reported their willingness to be vaccinated. With all significant covariates adjusted, older adults with moderate (aOR = 1.77, 95% CI: 1.04-3.04) and high level of social cohesion (aOR = 2.21, 95% CI: 1.29-3.77) were more likely to receive the booster dose. Our findings remained robust in a series of models after controlling for different covariates. Uncertainty about contraindications (38.3%), underestimation of their vulnerability (33.1%), and concerns about vaccine safety (32.0%) were the three main reasons for vaccine hesitancy. Therefore, building a harmonious community environment, strengthening neighborhood communication and exchange, and making good use of peer education among neighbors may become a breakthrough to promote herd immunity, especially for vulnerable older adults with limited social networks.

The Association between Risk Perception and Hesitancy toward the Booster Dose of COVID-19 Vaccine among People Aged 60 Years and Older in China.

BACKGROUND: Given the prevalence of the omicron variant and decreased immunity provided by vaccines, it is imperative to enhance resistance to COVID-19 in the old population. We planned to explore the hesitancy rate toward the booster dose of the COVID-19 vaccine and the association between risk perception and the abovementioned rate among people aged 60 and older. METHODS: This national cross-sectional study was conducted in mainland China from 25 May to 8 June 2022, targeting people who were 60 years old or above. Four dimensions were extracted from the Health Belief Model (HBM) to assess participants' perceived risk levels, including perceived susceptibility, perceived severity, perceived barriers, and perceived benefit. An independent Chi-square test was used to compare the vaccine hesitancy rates among different groups stratified by characteristics. Univariable and multivariable logistic regression models were performed to explore the associations between risk perception and hesitancy rate. RESULTS: Of 3321 participants, 17.2% (95% CI: 15.9-18.5%) were hesitant about booster shots of COVID-19 vaccines. Believing that they were ineligible for vaccination due to certain illnesses (38.3%), concern about vaccine safety (32.0%), believing the booster shots were unnecessary (33.1%), and their limitation on movements (28.0%) were the main reasons for vaccine hesitation. Adjusted by all the selected covariates, people with low perception level of susceptibility (aOR = 1.39, 95% CI: 1.00-1.92) and benefit (low: aOR = 3.31, 95% CI: 2.01-5.45; moderate: aOR = 2.23, 95% CI: 1.75-2.85) were less likely to receiving the booster dose, and the same results were found in people with higher perceived barriers (moderate: aOR = 2.67, 95% CI: 2.13-3.35; high: aOR = 2.04, 95% CI: 1.14-3.67). Our estimates were stable in all four models. CONCLUSIONS: In total, 17.2% of the people aged 60 years and older in China were hesitant about booster dose of COVID-19 vaccines, and it was closely associated with a lower level of perceived susceptibility and benefit, as well as a higher level of perceived barriers. Concerns about contraindications, vaccine safety, and limited movements were the main reasons for vaccine hesitancy. Targeted public health measure is a priority to improve the understanding of the elderly on their own susceptibility and vulnerability and clear the obstacles to vaccination.

Cost-effectiveness of interventions for the prevention and control of COVID-19: Systematic review of 85 modelling studies.

Background: We aimed to quantitatively summarise the health economic evaluation evidence of prevention and control programs addressing COVID-19 globally. Methods: We did a systematic review and meta-analysis to assess the economic and health benefit of interventions for COVID-19. We searched PubMed, Embase, Web of Science, and Cochrane Library of economic evaluation from December 31, 2019, to March 22, 2022, to identify relevant literature. Meta-analyses were done using random-effects models to estimate pooled incremental net benefit (INB). Heterogeneity was assessed using I2 statistics and publication bias was assessed by Egger's test. This study is registered with PROSPERO, CRD42021267475. Results: Of 16 860 studies identified, 85 articles were included in the systematic review, and 25 articles (10 studies about non-pharmacological interventions (NPIs), five studies about vaccinations and 10 studies about treatments) were included in the meta-analysis. The pooled INB of NPIs, vaccinations, and treatments were $1378.10 (95% CI = $1079.62, $1676.59), $254.80 (95% CI = $169.84, $339.77) and $4115.11 (95% CI = $1631.09, $6599.14), respectively. Sensitivity analyses showed similar findings. Conclusions: NPIs, vaccinations, and treatments are all cost-effective in combating the COVID-19 pandemic. However, evidence was mostly from high-income and middle-income countries. Further studies from lower-income countries are needed.

COVID-19 pandemic in BRICS countries and its association with socio-economic and demographic characteristics, health vulnerability, resources, and policy response.

BACKGROUND: Little attention has been paid to the comparison of COVID-19 pandemic responses and related factors in BRICS (Brazil, Russia, India, China, and South Africa) countries. We aimed at evaluating the association of daily new COVID-19 cases with socio-economic and demographic factors, health vulnerability, resources, and policy response in BRICS countries. METHODS: We conducted a cross-sectional study using data on the COVID-19 pandemic and other indicators of BRICS countries from February 26, 2020 to April 30, 2021. We compared COVID-19 epidemic in BRICS countries and analyzed related factors by log-linear Generalized Additive Model (GAM) models. RESULTS: In BRICS countries, India had the highest totally of confirmed cases with 18.76 million, followed by Brazil (14.45 million), Russia (4.81 million), and South Africa (1.58 million), while China (0.10 million) had the lowest figure. South Africa had the lowest rate of administered vaccine doses (0.18 million) among BRICS countries as of April 30, 2021. In the GAM model, a 1 unit increase in population density and policy stringency index was associated with a 5.17% and 1.95% growth in daily new COVID-19 cases (P < 0.001), respectively. Exposure-response curves for the effects of policy stringency index on daily new cases showed that there was a rapid surge in number of daily new COVID-19 cases when the index ranged from 0 to 45. The number of infections climbed slowly when the index ranged from 46 to 80, and decreased when the index was above 80 (P < 0.001). In addition, daily new COVID-19 cases (all P < 0.001) were also correlated with life expectancy at birth (-1.61%), extreme poverty (8.95%), human development index (-0.05%), GDP per capita (-0.18%), diabetes prevalence (0.66%), proportion of population aged 60 and above (2.23%), hospital beds per thousand people (-0.08%), proportion of people with access to improved drinking water (-7.40%), prevalence of open defecation (0.69%), and annual tourist/visitor arrivals (0.003%), after controlling other confounders. Different lag structures showed similar results in the sensitivity analysis. CONCLUSIONS: Strong policy response is crucial to control the pandemic, such as effective containment and case management. Our findings also highlighted the importance of reducing socio-economic inequalities and strengthening the resilience of health systems to better respond to public health emergencies globally.

Prevalence and impact of diabetes in patients with COVID-19 in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that has spread rapidly around the world. Previous studies have indicated that COVID-19 patients with diabetes are prone to having poor clinical outcomes. AIM: To systematically evaluate the prevalence of diabetes among COVID-19 patients in China and its impact on clinical outcomes, including ICU admission, progression to severe cases, or death. METHODS: We searched studies published in PubMed, Web of Science, and EMBASE from December 1, 2019 to March 31, 2020 to identify relevant observational study that investigated the prevalence of diabetes among COVID-19 patients or its impact on clinical outcomes. We used a random-effects or fixed-effects model to estimate the pooled prevalence of diabetes and risk ratio (RR) and its 95% confidence interval (CI) of diabetes on outcomes. Funnel plots were used to evaluate the publication bias and the heterogeneity was evaluated by I 2 statistic. RESULTS: Twenty-three eligible articles including 49564 COVID-19 patients (1573 with and 47991 without diabetes) were finally included. The pooled prevalence of diabetes was 10% (95%CI: 7%-15%) in COVID-19 patients. In the subgroup analyses, the pooled prevalence of diabetes was higher in studies with patients aged > 50 years (13%; 95%CI: 11%-16%) than in studies with patients aged ≤ 50 years (7%; 95%CI: 6%-8%), in severe patients (17%; 95%CI: 14%-20%) than in non-severe patients (6%; 95%CI: 5%-8%), and in dead patients (30%; 95%CI: 13%-46%) than in survivors (8%; 95%CI: 2%-15%) (P < 0.05 for all). Compared with patients without diabetes, the risk of severe cases was higher (RR = 2.13, 95%CI: 1.76-2.56, I 2 = 49%) in COVID-19 patients with diabetes. The risk of death was also higher in COVID-19 patients with diabetes (RR = 3.16, 95%CI: 2.64-3.78, I 2 = 34%). However, diabetes was not found to be significantly associated with admission to ICU (RR = 1.16, 95%CI: 0.15-9.11). CONCLUSION: Nearly one in ten COVID-19 patients have diabetes in China. Diabetes is associated with a higher risk of severe illness and death. The present study suggested that targeted early intervention is needed in COVID-19 patients with diabetes.