The Impacts of the COVID-19 Pandemic on Fertility Intentions of Women with Childbearing Age in China.

On 31 May 2021, the Political Bureau of the Central Committee of the Communist Party of China proposed the policy that a couple can have three children, and rolled out more supportive measures to further optimize the fertility policies. However, while the Chinese government is further optimizing its fertility policy, the sudden outbreak of COVID-19 is raging around the world, which threatens the implementation of China's fertility optimization policy. Based on this, this paper firstly explores the impact of COVID-19 on women's fertility intentions. Secondly, based on the Theory of Planned Behavior, this paper constructs a structural equation model to quantitatively reveal the specific factors that affect women's fertility intentions under the epidemic, as well as their impact paths, and then puts forward corresponding suggestions for the government to solve the problem of fertility, aiming at delaying population aging and optimizing population structure. The research results show that: (1) COVID-19 lowers the fertility intentions of women of childbearing age. (2) During the pandemic, economic pressure emerged as the biggest factor affecting women's fertility intentions. The decline in income caused by the pandemic has become an important factor in preventing women from having children. (3) The conflict between work and childbearing is still an important factor affecting the fertility intentions of women of childbearing age. The government's provision of perfect childcare services and their strengthening of the protection of women's employment rights and interests will greatly reduce women's anxiety about childbearing.

Epidemiology of rhinovirus under the COVID‐19 pandemic in Guangzhou, China, 2020

Background To analyze the epidemic characteristics of the human rhinovirus (HRV) outbreaks in Guangzhou, China, in 2020. Methods Descriptive epidemiological methods were used to analyze the HRV‐related outbreaks in Guangzhou, 2020. Results Seventeen outbreaks were reported in 2020 during the coronavirus disease 2019 (COVID‐19) pandemic in Guangzhou, a total of 465 patients (290 males and 175 females) were enrolled, with a median age of 10. A total of 223 (47.96%) had been tested for HRV, 89 (39.91%) of which were positive;344/465 (73.98%) had a fever, 138/465 (29.68%) had a runny nose, 139/465 (29.89%) had a sore throat, 86/465 (18.49%) had a cough, 41/465 (8.82%) had a headache, and 37/465 (7.96%) had a sneeze. Patients at age of 13–15 had the highest rate of sore throat and runny nose, patients aged 11–12 had the highest rate of sneezing, and patients at age of 12–14 had the highest rate of positive rate. Patients tested positive had a higher rate of fever (χ2 = 11.271, p = .001), cough (χ2 = 6.987, p = .008), runny nose (χ2 = 7.980, p = .005), and sneeze (χ2 = 4.676, p = .031). Conclusion The HRV was restored during the fighting of the COVID‐19 pandemic. The conventional COVID‐19 control measures were not effective enough in preventing rhinovirus. More appropriate control measures should be used to control HRV.

Epidemiology of rhinovirus under the COVID-19 pandemic in Guangzhou, China, 2020.

BACKGROUND: To analyze the epidemic characteristics of the human rhinovirus (HRV) outbreaks in Guangzhou, China, in 2020. METHODS: Descriptive epidemiological methods were used to analyze the HRV-related outbreaks in Guangzhou, 2020. RESULTS: Seventeen outbreaks were reported in 2020 during the coronavirus disease 2019 (COVID-19) pandemic in Guangzhou, a total of 465 patients (290 males and 175 females) were enrolled, with a median age of 10. A total of 223 (47.96%) had been tested for HRV, 89 (39.91%) of which were positive; 344/465 (73.98%) had a fever, 138/465 (29.68%) had a runny nose, 139/465 (29.89%) had a sore throat, 86/465 (18.49%) had a cough, 41/465 (8.82%) had a headache, and 37/465 (7.96%) had a sneeze. Patients at age of 13-15 had the highest rate of sore throat and runny nose, patients aged 11-12 had the highest rate of sneezing, and patients at age of 12-14 had the highest rate of positive rate. Patients tested positive had a higher rate of fever (χ2 = 11.271, p = .001), cough (χ2 = 6.987, p = .008), runny nose (χ2 = 7.980, p = .005), and sneeze (χ2 = 4.676, p = .031). CONCLUSION: The HRV was restored during the fighting of the COVID-19 pandemic. The conventional COVID-19 control measures were not effective enough in preventing rhinovirus. More appropriate control measures should be used to control HRV.

Comparison of ARIMA, ES, GRNN and ARIMA–GRNN hybrid models to forecast the second wave of COVID-19 in India and the United States

As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.

The SARS-CoV-2 outbreak: what we know. (Coronavirus (COVID-19) collection.)

There is a current worldwide outbreak of the novel coronavirus Covid-19 (coronavirus disease 2019;the pathogen called SARS-CoV-2;previously 2019-nCoV), which originated from Wuhan in China and has now spread to 6 continents including 66 countries, as of 24:00 on March 2, 2020. Governments are under increased pressure to stop the outbreak from spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak site and from laboratories supporting the investigation. This paper aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus.

Spike-specific circulating T follicular helper cell and cross-neutralizing antibody responses in COVID-19-convalescent individuals.

Coronavirus disease 2019 (COVID-19) is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1-3 and individuals with COVID-19 have symptoms that can be asymptomatic, mild, moderate or severe4,5. In the early phase of infection, T- and B-cell counts are substantially decreased6,7; however, IgM8-11 and IgG12-14 are detectable within 14 d after symptom onset. In COVID-19-convalescent individuals, spike-specific neutralizing antibodies are variable3,15,16. No specific drug or vaccine is available for COVID-19 at the time of writing; however, patients benefit from treatment with serum from COVID-19-convalescent individuals17,18. Nevertheless, antibody responses and cross-reactivity with other coronaviruses in COVID-19-convalescent individuals are largely unknown. Here, we show that the majority of COVID-19-convalescent individuals maintained SARS-CoV-2 spike S1- and S2-specific antibodies with neutralizing activity against the SARS-CoV-2 pseudotyped virus, and that some of the antibodies cross-neutralized SARS-CoV, Middle East respiratory syndrome coronavirus or both pseudotyped viruses. Convalescent individuals who experienced severe COVID-19 showed higher neutralizing antibody titres, a faster increase in lymphocyte counts and a higher frequency of CXCR3+ T follicular help (TFH) cells compared with COVID-19-convalescent individuals who experienced non-severe disease. Circulating TFH cells were spike specific and functional, and the frequencies of CXCR3+ TFH cells were positively associated with neutralizing antibody titres in COVID-19-convalescent individuals. No individuals had detectable autoantibodies. These findings provide insights into neutralizing antibody responses in COVID-19-convalescent individuals and facilitate the treatment and vaccine development for SARS-CoV-2 infection.

The SARS-CoV-2 outbreak: What we know.

There is a current worldwide outbreak of the novel coronavirus Covid-19 (coronavirus disease 2019; the pathogen called SARS-CoV-2; previously 2019-nCoV), which originated from Wuhan in China and has now spread to 6 continents including 66 countries, as of 24:00 on March 2, 2020. Governments are under increased pressure to stop the outbreak from spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak site and from laboratories supporting the investigation. This paper aggregates and consolidates the epidemiology, clinical manifestations, diagnosis, treatments and preventions of this new type of coronavirus.