Trend Dynamics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Transmission in 16 Cities of Hubei Province, China.

OBJECTIVE: A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected by researchers from a patient in Wuhan, Hubei province, China, in December 2019, and broke out in January 2020. Then, the pandemic was detected in countries around the world. Therefore, precise estimates of its current and future trends are highly required for future policy implications. METHODS: We retrieved data from the Health Commission of Hubei, China. Logistic-S curve model was used to estimate the current and future trends of SARS-CoV-2-infected cases among 16 cities of Hubei, China from Jan-11 to Feb-24, 2020. RESULTS: Out of 64,287 confirmed cases of SARS-CoV-2 infection in Hubei, higher percentage of cases were in Wuhan and Xiaogan. The highest death percentage was found in Wuhan and Qianjiang. A significant percentage of cures were found in Enshi Prefecture and Huanggang, while Wuhan showed the lowest percentage of cures. Rising trends in infected cases were observed throughout the study period, particularly in Wuhan, and a higher trend was observed after 12-Feb. Gradual decline trend of SARS-CoV-2 cases was observed during Feb-25 to Mar-15 in Hubei Province. Future forecast showed that the average number of SARS-CoV-2-infected cases might be decreased or stable in Hubei in the coming 20 days. CONCLUSION: The public must take precautionary measures in order to control and prevent disease spread and avoid extra travelling.

Long-Term Changes of HIV/AIDS Incidence Rate in China and the U.S. Population From 1994 to 2019: A Join-Point and Age-Period-Cohort Analysis.

Although HIV caused one of the worst epidemics since the late twentieth century, China and the U.S. has made substantial progress to control the spread of HIV/AIDS. However, the trends of HIV/AIDS incidence remain unclear in both countries. Therefore, this study aimed to highlight the long-term trends of HIV/AIDS incidence by gender in China and the U.S. population. The data were retrieved from the Global Burden of Disease (GBD) database since it would be helpful to assess the impact/role of designed policies in the control of HIV/AIDS incidence in both countries. The age-period-cohort (APC) model and join-point regression analysis were employed to estimate the age-period-cohort effect and the average annual percentage change (AAPC) on HIV incidence. Between 1994 and 2019, we observed an oscillating trend of the age-standardized incidence rate (ASIR) in China and an increasing ASIR trend in the U.S. Despite the period effect in China declined for both genders after peaked in 2004, the age effect in China grew among the young (from 15-19 to 25-29) and the old age groups (from 65-69 to 75-79). Similarly, the cohort effect increased among those born in the early (from 1924-1928 to 1934-1938) and the latest birth groups (from 1979-1983 to 2004-2009). In the case of the U.S., the age effect declined after it peaked in the 25-29 age group. People born in recent birth groups had a higher cohort effect than those born in early groups. In both countries, women were less infected by HIV than men. Therefore, besides effective strategies and awareness essential to protect the young age groups from HIV risk factors, the Chinese government should pay attention to the elderly who lacked family support and were exposed to HIV risk factors.

The Association of Hypertension With the Severity of and Mortality From the COVID-19 in the Early Stage of the Epidemic in Wuhan, China: A Multicenter Retrospective Cohort Study.

Background: Hypertension may affect the prognosis of COVID-19 illness. We analyzed the epidemiological and clinical characteristics associated with the disease severity and mortality in hypertensive vs. non-hypertensive deceased COVID-19 patients. Methods: We included all the deceased patients with laboratory-confirmed COVID-19 admitted to >200 health facilities in Wuhan between December 1 and February 24, 2020. The median survival time in COVID-19 patients with and without hypertension, the association of hypertension with the disease severity, and the risk factors associated with the COVID-19 mortality stratified by the hypertension status were assessed using the Kaplan-Meier survival analysis, logistic regression, and Cox proportional regression, respectively before and after the propensity score-matching (PS) for age and sex. Results: The prevalence of hypertension in the studied 1,833 COVID-19 patients was 40.5%. Patients with hypertension were more likely to have severe COVID-19 illness than patients without hypertension; the PS-matched multivariable-adjusted odds ratio (95% CI) was 2.44 (1.77-3.08). Moreover, the median survival time in the hypertension group was 3-5 days shorter than the non-hypertension group. There was a 2-fold increased risk of COVID-19 mortality in the hypertension group compared with the non-hypertension group; the PS-matched multivariable-adjusted hazard ratio (HR) = 2.04 (1.61-2.72), and the significant increased risk of COVID-19 mortality in the moderate vs. mild COVID-19 illness was confined to patients with hypertension. Additionally, the history and the number of underlying chronic diseases, occupation, and residential location showed stronger associations with the COVID-19 mortality among patients with hypertension than patients without hypertension. Conclusion: Hypertension was associated with the severity and mortality of COVID-19 illness.

The comparison of epidemiological characteristics between confirmed and clinically diagnosed cases with COVID-19 during the early epidemic in Wuhan, China.

BACKGROUND: To put COVID-19 patients into hospital timely, the clinical diagnosis had been implemented in Wuhan in the early epidemic. Here we compared the epidemiological characteristics of laboratory-confirmed and clinically diagnosed cases with COVID-19 in Wuhan. METHODS: Demographics, case severity and outcomes of 29,886 confirmed cases and 21,960 clinically diagnosed cases reported between December 2019 and February 24, 2020, were compared. The risk factors were estimated, and the effective reproduction number (Rt) of SARS-CoV-2 was also calculated. RESULTS: The age and occupation distribution of confirmed cases and clinically diagnosed cases were consistent, and their sex ratio were 1.0 and 0.9, respectively. The epidemic curve of clinical diagnosis cases was similar to that of confirmed cases, and the city centers had more cumulative cases and higher incidence density than suburbs in both of two groups. The proportion of severe and critical cases (21.5 % vs. 14.0 %, P < 0.0001) and case fatality rates (5.2 % vs. 1.2 %, P < 0.0001) of confirmed cases were all higher than those of clinically diagnosed cases. Risk factors for death we observed in both of two groups were older age, male, severe or critical cases. Rt showed the same trend in two groups, it dropped below 1.0 on February 6 among confirmed cases, and February 8 among clinically diagnosed cases. CONCLUSIONS: The demographic characteristics and spatiotemporal distributions of confirmed and clinically diagnosed cases are roughly similar, but the disease severity and clinical outcome of clinically diagnosed cases are better than those of confirmed cases. In cases when detection kits are insufficient during the early epidemic, the implementation of clinical diagnosis is necessary and effective.

Statistical analysis of COVID-19 infection caused by environmental factors: Evidence from Pakistan.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a severe public health problem around the globe. Various epidemiological, statistical, and laboratory-based studies have shown that the role of temperature and other environmental factors has important influence in the transmission of coronaviruses. Scientific research is needed to answer the questions about the spread and transmission of the infection, whether people could be avoided from being infected with COVID-19 in next summer. AIM: We aim to investigate the association of daily average temperature, daily average dew point, daily average humidity, daily average wind speed, and daily average pressure with the infection caused by this novel coronavirus in Pakistan. KEY FINDINGS: First, we check the correlation between environmental factors and daily infected cases of COVID-19; among them, temperature and dew point have positive linear relationship with daily infected cases of COVID-19. The thought-provoking findings of the present study suggested that higher temperature and dew point can contribute to a rise in COVID-19 disease in four provinces of Pakistan, possible to genome modifications and viral resistance to harsh environment. Moreover, it is also observed that humidity in Punjab and Sindh, and wind speed in Balochistan and Khyber Pakhtunkhwa have influenced the spreading of daily infected COVID-19 cases. SIGNIFICANCE: Current study will serve as a guideline to develop understanding of environmental factors that influence COVID-19 spread, helping policymakers to prepare and handle a catastrophe resulting from this pandemic.

The epidemiological characteristics of deaths with COVID-19 in the early stage of epidemic in Wuhan, China.

OBJECTIVES: To analyze the epidemiological characteristics of COVID-19 related deaths in Wuhan, China and comprehend the changing trends of this epidemic along with analyzing the prevention and control measures in Wuhan. METHODS: Through the China's Infectious Disease Information System, we collected information about COVID-19 associated deaths from December 15, 2019 to February 24, 2020 in Wuhan. We analyzed the patient's demographic characteristics, drew epidemiological curve and made geographic distribution maps of the death toll in each district over time, etc. ArcGIS was used to plot the numbers of daily deaths on maps. Statistical analyses were performed using SPSS and @Risk software. RESULTS: As of February 24, 2020, a total of 1833 deaths were included. Among the deaths with COVID-19, mild type accounted for the most (37.2%), followed by severe type (30.1%). The median age was 70.0 (inter quartile range: 63.0-79.0) years. Most of the deaths were distributed in 50-89 age group, whereas no deaths occurred in 0-9 age group. Additionally, the male to female ratio was 1.95:1. A total of 65.7% of the deaths in Wuhan combined with underlying diseases, and was more pronounced among males. Most of the underlying diseases included hypertension, diabetes and cardiovascular diseases. The peak of daily deaths appeared on February 14 and then declined. The median interval from symptom onset to diagnosis was 10.0 (6.0-14.0) days; the interval from onset to diagnosis gradually shortened. The median intervals from diagnosis to death and symptom onset to deaths were 6.0 (2.0-11.0), 17.0 (12.0-22.0) days, respectively. Most of the disease was centralized in central urban area with highest death rate in Jianghan District. CONCLUSION: COVID-19 poses a greater threat to the elderly people and men with more devastating effects, particularly in the presence of underlying diseases. The geographical distributions show that the epidemic in the central area of Wuhan is more serious than that in the surrounding areas. Analysis of deaths as of February 24 indicates that a tremendous improvement of COVID-19 epidemic in Wuhan has achieved by effective control measures taken by Wuhan Government.

Epidemiological characteristics of patients with severe COVID-19 infection in Wuhan, China: evidence from a retrospective observational study.

BACKGROUND: The new coronavirus (COVID-19) rapidly resulted in a pandemic. We report the characteristics of patients with severe or critical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in Wuhan city, China, and the risk factors related to infection severity and death. METHODS: We extracted the demographic and clinical data of 7283 patients with severe COVID-19 infection from designated Wuhan hospitals as of 25 February 2020. Factors associated with COVID-19 critical illness and mortality were analysed using logistic- and Cox-regression analyses. RESULTS: We studied 6269 patients with severe COVID-19 illness and 1014 critically ill patients. The median (IQR) age was 64 (53-71) years; 51.2% were male, 38.9% were retirees and 7.4% had self-reported histories of chronic disease. Up to the end of the study, 1180 patients (16.2%) recovered and were discharged, 649 (8.9%) died and the remainder were still receiving treatment. The number of daily confirmed critical cases peaked between 23 January and 1 February 2020. Patients with advanced age [odds ratio (OR), 1.03; 95% confidence intervals (CIs), 1.03-1.04], male sex (OR, 1.57; 95% CI, 1.33-1.86) and pre-existing diabetes (OR, 2.11), hypertension (OR, 2.72), cardiovascular disease (OR, 2.15) or respiratory disease (OR, 3.50) were more likely to be critically ill. Compared with those who recovered and were discharged, patients who died were older [hazard ratio (HR), 1.04; 95% CI, 1.03-1.05], more likely to be male (HR, 1.74; 95% CI, 1.44-2.11) and more likely to have hypertension (HR, 5.58), cardiovascular disease (HR, 1.83) or diabetes (HR, 1.67). CONCLUSION: Advanced age, male sex and a history of chronic disease were associated with COVID-19 critical illness and death. Identifying these risk factors could help in the clinical monitoring of susceptible populations.

Unraveling the Epidemiology, Geographical Distribution, and Genomic Evolution of Potentially Lethal Coronaviruses (SARS, MERS, and SARS CoV-2).

SARS CoV appeared in 2003 in China, transmitted from bats to humans via eating infected animals. It affected 8,096 humans with a death rate of 11% affecting 21 countries. The receptor binding domain (RBD) in S protein of this virus gets attached with the ACE2 receptors present on human cells. MERS CoV was first reported in 2012 in Middle East, originated from bat and transmitted to humans through camels. MERS CoV has a fatality rate of 35% and last case reported was in 2017 making a total of 1,879 cases worldwide. DPP4 expressed on human cells is the main attaching site for RBD in S protein of MERS CoV. Folding of RBD plays a crucial role in its pathogenesis. Virus causing COVID-19 was named as SARS CoV-2 due its homology with SARS CoV that emerged in 2003. It has become a pandemic affecting nearly 200 countries in just 3 months' time with a death rate of 2-3% currently. The new virus is fast spreading, but it utilizes the same RBD and ACE2 receptors along with furin present in human cells. The lessons learned from the SARS and MERS epidemics are the best social weapons to face and fight against this novel global threat.