The global impact of COVID-19 on abortion care.

Background: The COVID-19 pandemic placed unprecedented strain on healthcare globally, which exacerbated factors leading to unplanned pregnancies. Objectives: The primary objective was to analyze the effect of COVID-19 on abortion services globally. Secondary objectives were to discuss issues regarding access to safe abortion and provide recommendations on continued access during pandemics. Search strategy: A search for relevant articles was conducted by utilizing multiple databases (PubMed, Cochrane, etc.). Selection criteria: Studies on COVID-19 and abortion were included. Data collection & analysis: The legislation governing abortion services across the globe was examined, inclusive of modifications to service provision during the pandemic. Global data on abortion rates and analyses of selected articles were also included. Main results: 14 countries instituted legislative changes related to the pandemic, 11 relaxed abortion regulations, while three restricted abortion access. An increase in abortion rates was seen particularly where telemedicine was available. Where abortions were postponed, second-trimester abortions increased after services resumed. Conclusions: Legislation, risk of exposure to infection, and access to telemedicine affect access to abortion. The use of novel technologies, maintaining existing infrastructure and enhancing the roles of trained manpower for safe abortion access is recommended to avoid the marginalization of women's health and reproductive rights.

Healthcare workers' self-regulatory eating behaviours are associated with being stress-free during the Covid-19 lockdown in Singapore.

Our study sought to examine the impact of the pandemic and the Circuit-breaker (CB) measures on dietary behaviours of healthcare workers (HCW). In addition, the association between self-regulatory eating behaviours and psychological stress was explored. Our study employed a cross-sectional anonymous survey that examined the demographics, dietary habits, self-regulatory eating behaviours (SR) and their association to stress levels of healthcare workers (HCWs) before and during the Circuit Breaker (CB) in Singapore. The survey was conducted over four weeks from May 17 to June 18, 2020. Snowball sampling was performed in the final week. A total of 707 participants took part in the survey. Due to the CB measures and modifications of work scope and work areas, there were significant changes in their dietary behaviors before CB versus during the CB period (n = 707), with many reducing the intake of vegetables (p = 0.018) while increasing their intake of unhealthy food choices such as canned drinks (p = 0.002), convenience food (p ≤ 0.001) and alcoholic drinks (p = 0.034). Before the CB period, 91.8% (602/656) of participants who intended to have a healthy diet were classified in medium-to-high SR groups whereas during the CB period, 87.7% (575/656) were in medium-to-high SR groups and the difference was statistically significant (p = 0.011). Nurses, administrative staff, HCWs of Chinese and Indian ethnicities, staff who did not complete university education and those who did not have domestic helpers were more likely to have reduced SR. Importantly, amongst participants who intended to have a healthy diet, 70.9% displayed no change or improved eating habits and showed medium-to-high levels of SR during CB. Participants with no changes in SR were 2.11 times more likely to be stress-free as compared to those who had deteriorated SR (OR 2.11 95% CI 1.27-3.48, p = 0.004). Due to CB measures and work modifications, dietary behaviours of HCWs deteriorated with increased intake of unhealthy food choices. HCWs who maintain their self-regulatory eating behaviour are more likely to be stress-free. Short screening questionnaires based on SR changes should be developed and explored as surveillance tools for assessment of HCWs' general well-being such that personalized interventions to vulnerable groups of workers could be implemented effectively on the ground.

Comparison of PM2.5 and CO2 Concentrations in Large Cities of China during the COVID-19 Lockdown.

Estimating the impacts on PM2.5 pollution and CO2 emissions by human activities in different urban regions is important for developing efficient policies. In early 2020, China implemented a lockdown policy to contain the spread of COVID-19, resulting in a significant reduction of human activities. This event presents a convenient opportunity to study the impact of human activities in the transportation and industrial sectors on air pollution. Here, we investigate the variations in air quality attributed to the COVID-19 lockdown policy in the megacities of China by combining in-situ environmental and meteorological datasets, the Suomi-NPP/VIIRS and the CO2 emissions from the Carbon Monitor project. Our study shows that PM2.5 concentrations in the spring of 2020 decreased by 41.87% in the Yangtze River Delta (YRD) and 43.30% in the Pearl River Delta (PRD), respectively, owing to the significant shutdown of traffic and manufacturing industries. However, PM2.5 concentrations in the Beijing-Tianjin-Hebei (BTH) region only decreased by 2.01% because the energy and steel industries were not fully paused. In addition, unfavorable weather conditions contributed to further increases in the PM2.5 concentration. Furthermore, CO2 concentrations were not significantly affected in China during the short-term emission reduction, despite a 19.52% reduction in CO2 emissions compared to the same period in 2019. Our results suggest that concerted efforts from different emission sectors and effective long-term emission reduction strategies are necessary to control air pollution and CO2 emissions.

Effects of acute severe acute respiratory syndrome coronavirus 2 infection on male hormone profile, ACE2 and TMPRSS2 expression, and potential for transmission of severe acute respiratory syndrome coronavirus 2 in semen of Asian men.

OBJECTIVE: To confirm if severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be detected in semen of men with acute coronavirus disease 2019 and if their male hormone profile (testosterone, follicle-stimulating hormone, luteinizing hormone, sex hormone binding globulin, and free androgen index) is adversely affected during the acute phase of infection and any relation to the ACE2 and/or TMPRSS2 expression in human semen. DESIGN: Clinical study. SETTING: National University Hospital, Singapore. PATIENTS: Asian men aged 21-55 years who were admitted to National University Hospital, Singapore, with a laboratory-confirmed diagnosis of SARS-CoV-2 infection via nasopharyngeal swab in the acute phase of the infection, within 2-14 days of the development of symptoms or contact history, were recruited for the study. INTERVENTIONS: Blood was collected in the morning to assess the male hormone profile. Human semen were obtained by masturbation and sent to the molecular diagnostic laboratories to detect the presence of SARS-CoV-2 RNA and assess the ACE2 and TMPRSS2 expression. MAIN OUTCOME MEASURES: Male hormone profile level and expression of SARS-CoV-2 RNA, ACE2, and TMPRSS2 in human semen. RESULTS: A total of 63 men of Asian ethnicities agreed to participate in the study. Subsequently, 65% of recruited men had completely normal levels of male hormone profile. Moreover, 27% were noted to have higher luteinizing hormone levels between 6.6 and 16.1 IU/L (normal range, 0.8-6.1 IU/L), and 10% had higher follicle-stimulating hormone levels between 13.6 and 41.6 IU/L (normal range, 1.5-12.4 IU/L); all had normal testosterone levels. No SARS-CoV-2 RNAs were detected in all human semen. The ACE2 and TMPRSS2 expression was undetectable in 26 samples, whereas 23 samples only had a detectable TMPRSS2 expression and 4 only had an ACE2 expression. The remaining 3 expressed both ACE2 and TMPRSS2. CONCLUSIONS: Severe acute respiratory syndrome coronavirus 2 could not be found in the semen of a cohort of young to middle-aged Asian men with mild acute SARS-CoV-2 infection. However, there was a detectable expression of ACE2 and TMPRSS2 in semen, although not causal, and it may be correlated to changes in male hormone profiles and male age.

Multi-center sparse learning and decision fusion for automatic COVID-19 diagnosis.

The coronavirus disease 2019 (COVID-19) pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a sharp increase in hospitalized patients with multi-organ disease pneumonia. Early and automatic diagnosis of COVID-19 is essential to slow down the spread of this epidemic and reduce the mortality of patients infected with SARS-CoV-2. In this paper, we propose a joint multi-center sparse learning (MCSL) and decision fusion scheme exploiting chest CT images for automatic COVID-19 diagnosis. Specifically, considering the inconsistency of data in multiple centers, we first convert CT images into histogram of oriented gradient (HOG) images to reduce the structural differences between multi-center data and enhance the generalization performance. We then exploit a 3-dimensional convolutional neural network (3D-CNN) model to learn the useful information between and within 3D HOG image slices and extract multi-center features. Furthermore, we employ the proposed MCSL method that learns the intrinsic structure between multiple centers and within each center, which selects discriminative features to jointly train multi-center classifiers. Finally, we fuse these decisions made by these classifiers. Extensive experiments are performed on chest CT images from five centers to validate the effectiveness of the proposed method. The results demonstrate that the proposed method can improve COVID-19 diagnosis performance and outperform the state-of-the-art methods.

Physical activity levels and mental health burden of healthcare workers during COVID-19 lockdown.

The outbreak of COVID-19 has precipitated international lockdown measures to curb disease transmissions. The closure of public activity spaces as well as changes in pandemic workload may disrupt healthcare workers' physical activity and self-care routines. We sought to examine the association between physical activity levels and mental health burden of healthcare workers during the COVID-19 lockdown in Singapore. This cross-sectional study comprised of an multidomain survey that was administered digitally to 707 healthcare workers between 17 May and 18 June 2020. Exercise frequency, duration and intensity of these healthcare workers had reduced significantly during the lockdown compared to pre-lockdown. 25.3%, 37.2%, and 11.9% had screened positive for moderate-to-extremely-severe depression, anxiety and stress respectively. Reductions in exercise duration was a significant risk factor for mild stress and moderate-to-severe depression while increase in exercise frequency was found to be a protective factor against depressed mood. Our study revealed that a short-term reduction in physical activity levels during lockdown was associated with poorer psychological outcomes. Given the protection that exercise confers on depression, physical activity should be promoted at the workplace and at home to support healthcare workers to cope through this protracted health crisis.

The role of seasonality in the spread of COVID-19 pandemic.

It has been reported that the transmission of COVID-19 can be influenced by the variation of environmental factors due to the seasonal cycle. However, its underlying mechanism in the current and onward transmission pattern remains unclear owing to the limited data and difficulties in separating the impacts of social distancing. Understanding the role of seasonality in the spread of the COVID-19 pandemic is imperative in formulating public health interventions. Here, the seasonal signals of the COVID-19 time series are extracted using the EEMD method, and a modified Susceptible, Exposed, Infectious, Recovered (SEIR) model incorporated with seasonal factors is introduced to quantify its impact on the current COVID-19 pandemic. Seasonal signals decomposed via the EEMD method indicate that infectivity and mortality of SARS-CoV-2 are both higher in colder climates. The quantitative simulation shows that the cold season in the Southern Hemisphere countries caused a 59.71 ± 8.72% increase of the total infections, while the warm season in the Northern Hemisphere countries contributed to a 46.38 ± 29.10% reduction. COVID-19 seasonality is more pronounced at higher latitudes, where larger seasonal amplitudes of environmental indicators are observed. Seasonality alone is not sufficient to curb the virus transmission to an extent that intervention measures are no longer needed, but health care capacity should be scaled up in preparation for new surges in COVID-19 cases in the upcoming cold season. Our study highlights the necessity of considering seasonal factors when formulating intervention strategies.

Optimal temperature zone for the dispersal of COVID-19.

It is essential to know the environmental parameters within which the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can survive to understand its global dispersal pattern. We found that 60.0% of the confirmed cases of coronavirus disease 2019 (COVID-19) occurred in places where the air temperature ranged from 5 °C to 15 °C, with a peak in cases at 11.54 °C. Moreover, approximately 73.8% of the confirmed cases were concentrated in regions with absolute humidity of 3 g/m3 to 10 g/m3. SARS-CoV-2 appears to be spreading toward higher latitudes. Our findings suggest that there is an optimal climatic zone in which the concentration of SARS-CoV-2 markedly increases in the ambient environment (including the surfaces of objects). These results strongly imply that the COVID-19 pandemic may spread cyclically and outbreaks may recur in large cities in the mid-latitudes in autumn 2020.