Association between meteorological factors and COVID-19 transmission in low- and middle-income countries: A time-stratified case-crossover study.

BACKGROUND: Evidence is limited regarding the association between meteorological factors and COVID-19 transmission in low- and middle-income countries (LMICs). OBJECTIVE: To investigate the independent and interactive effects of temperature, relative humidity (RH), and ultraviolet (UV) radiation on the spread of COVID-19 in LMICs. METHODS: We collected daily data on COVID-19 confirmed cases, meteorological factors and non-pharmaceutical interventions (NPIs) in 2143 city- and district-level sites from 6 LMICs during 2020. We applied a time-stratified case-crossover design with distributed lag nonlinear model to evaluate the independent and interactive effects of meteorological factors on COVID-19 transmission after controlling NPIs. We generated an overall estimate through pooling site-specific relative risks (RR) using a multivariate meta-regression model. RESULTS: There was a positive, non-linear, association between temperature and COVID-19 confirmed cases in all study sites, while RH and UV showed negative non-linear associations. RR of the 90th percentile temperature (28.1 °C) was 1.14 [95% confidence interval (CI): 1.02, 1.28] compared with the 50th percentile temperature (24.4 °C). RR of the10th percentile UV was 1.41 (95% CI: 1.29, 1.54). High temperature and high RH were associated with increased risks in temperate climate but decreased risks in tropical climate, while UV exhibited a consistent, negative association across climate zones. Temperature, RH, and UV interacted to affect COVID-19 transmission. Temperature and RH also showed higher risks in low NPIs sites. CONCLUSION: Temperature, RH, and UV appeared to independently and interactively affect the transmission of COVID-19 in LMICs but such associations varied with climate zones. Our results suggest that more attention should be paid to meteorological variation when the transmission of COVID-19 is still rampant in LMICs.

Exploration on wastewater-based epidemiology of SARS-CoV-2: Mimic relative quantification with endogenous biomarkers as internal reference.

Wastewater-based epidemiology has become a powerful surveillance tool for monitoring the pandemic of COVID-19. Although it is promising to quantitatively correlate the SARS-CoV-2 RNA concentration in wastewater with the incidence of community infection, there is still no consensus on whether the viral nucleic acid concentration in sewage should be normalized against the abundance of endogenous biomarkers and which biomarker should be used as a reference for the normalization. Here, several candidate endogenous reference biomarkers for normalization of SARS-CoV-2 signal in municipal sewage were evaluated. The human fecal indicator virus (crAssphage) is a promising candidate of endogenous reference biomarker for data normalization of both DNA and RNA viruses for its intrinsic viral nature and high and stable content in sewage. Without constructing standard curves, the relative quantification of sewage viral nucleic acid against the abundance of the reference biomarker can be used to correlate with community COVID-19 incidence, which was proved via mimic experiments by spiking pseudovirus of different concentrations in sewage samples. Dilution of pseudovirus-seeded wastewater did not affect the relative abundance of viral nucleic acid, demonstrating that relative quantification can overcome the sewage dilution effects caused by the greywater input, precipitation and/or groundwater infiltration. The process of concentration, recovery and detection of the endogenous biomarker was consistent with that of SARS-CoV-2 RNA. Thus, it is necessary to co-quantify the endogenous biomarker because it can be not only an internal reference for data normalization, but also a process control.

Epidemiological survey of an epidemic of COVID-19 due to occupational exposure in Qinghai, 2021

Objective: To analyze the epidemiological characteristics of an epidemic of coronavirus disease 2019 (COVID-19) caused by occupational exposure in Xining, Qinghai province, from October 17 to November 2, 2021 and provide evidence for the prevention and control of COVID-19 epidemic. Methods: In accordance with the requirements of the COVID-19 prevention and control protocol (eighth edition), epidemiological survey and field response were conducted and throat swabs were collected from the confirmed cases and close contacts. Real time-PCR(RT-PCR) was used to detect severe acute respiratory syndrome coronavirus (SARS-CoV-2) nucleic acid. Gene sequencing was performed for the throat swabs of partial confirmed cases by high throughput sequencing. Results: A total of 11 COVID-19 cases were reported in this epidemic, including 3 cases in a family and 8 cases in medical staff. Nine cases were women, 2 cases were men. The cases in epidemic had 3 generations. The average incubation period was 3.18 day. The infection was mainly occurred in working place. The risk factors included sharing telephone, computer and other office equipment. The initial symptoms were cough (10 cases, 90.97%). Unstandardized taking off protective suit in field epidemiological survey and inappropriate design of waterproof boot cover were the main risk factors for the occupational exposure. The SARS-CoV-2 detected belonged to VOC/Delta variant. Conclusion: This epidemic was caused by occupational exposure. It is suggested to strengthen the field supervision and guide of the wearing of protective suits, improve the design of waterproof boot cover and reduce the contacts of field workers with others.

Development of a model by LASSO to predict hospital length of stay (LOS) in patients with the SARS-Cov-2 omicron variant.

The length of stay (LOS) in hospital varied considerably in different patients with COVID-19 caused by SARS-CoV-2 Omicron variant. The study aimed to explore the clinical characteristics of Omicron patients, identify prognostic factors, and develop a prognostic model to predict the LOS of Omicron patients. This was a single center retrospective study in a secondary medical institution in China. A total of 384 Omicron patients in China were enrolled. According to the analyzed data, we employed LASSO to select the primitive predictors. The predictive model was constructed by fitting a linear regression model using the predictors selected by LASSO. Bootstrap validation was used to test performance and eventually we obtained the actual model. Among these patients, 222 (57.8%) were female, the median age of patients was 18 years and 349 (90.9%) completed two doses of vaccination. Patients on admission diagnosed as mild were 363 (94.5%). Five variables were selected by LASSO and a linear model, and those with P < 0.05 were integrated into the analysis. It shows that if Omicron patients receive immunotherapy or heparin, the LOS increases by 36% or 16.1%. If Omicron patients developed rhinorrhea or occur familial cluster, the LOS increased by 10.4% or 12.3%, respectively. Moreover, if Omicron patients' APTT increased by one unit, the LOS increased by 0.38%. Five variables were identified, including immunotherapy, heparin, familial cluster, rhinorrhea, and APTT. A simple model was developed and evaluated to predict the LOS of Omicron patients. The formula is as follows: Predictive LOS = exp(1*2.66263 + 0.30778*Immunotherapy + 0.1158*Familiar cluster + 0.1496*Heparin + 0.0989*Rhinorrhea + 0.0036*APTT).

Estimation and sensitivity analysis of a COVID-19 model considering the use of face mask and vaccination.

To model the COVID-19 infection and develop effective control measures, this paper proposes an SEIR-type epidemic model considering the impact of face-mask wearing and vaccination. Firstly, the effective reproduction number and the threshold conditions are obtained. Secondly, based on the data of South Korea from January 20, 2022 to March 21, 2022, the model parameters are estimated. Finally, a sensitivity analysis and the numerical study are conducted. The results show that the face-mask wearing is associated with [Formula: see text] and [Formula: see text] reductions in the numbers of cumulative cases and newly confirmed cases, respectively, after a period of 60 days, when the face mask wearing rate increases by [Formula: see text]. Furthermore, the vaccination rate is associated with [Formula: see text] and [Formula: see text] reductions in the numbers of cumulative cases and the newly confirmed cases, respectively, after the same period of 60 days when the vaccination rate is increased by [Formula: see text]. A combined measure involving face-mask wearing and vaccination may be more effective and reasonable in preventing and controlling this infection. It is also suggested that disease control departments should strongly recommended the wearing of face masks s as well as vaccination to prevent the unvaccinated people from becoming infected.

Source tracing of the COVID-19 infection case in Guangxi, China

The study describing the process of discovery and source tracing of a native case of coronavirus disease 2019 (COVID-19) infection on Jan 2021, in Guangxi, China, to provide methodology for source investigation better in the future. Following the Epidemiological Investigation Plan for COVID-19 (version 7), information of the native COVID-19 case and related close contacts were collected. Real time reverse transcription-quantitative polymerase chain reaction was performed to detect the nucleic acids of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in samples collected from the infection case, related close contacts, and the environment, combined with serum specific antibody detection. The positive nucleic acid samples were undergone whole genome sequencing, phylogenetic analysis and analyses of variation of amino acids. The whole genome sequence from the native case and the imported asymptomatic infected case from Indonesia containing 25 nucleotide mutation sites belong to L-Lineage European Branch II. 3. The imported asymptomatic case was the source of infection of this native case. The possible route of infection was that native case was exposed to contaminated environment by imported case, due to improper personal protective equipment. A focus on local outbreaks of COVID-19 caused by SARS-CoV-2-infected people from outside China is needed.

Comparison of clinical characteristics between SARS-CoV-2 Omicron variant and Delta variant infections in China.

Background: The continued 'evolution' of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of the Omicron variant after the Delta variant, resulting in a significant increase in the number of people with COVID-19. This increase in the number of cases continues to have a significant impact on lives. Therefore, a more detailed understanding of the clinical characteristics of Omicron infection is essential. Methods: Using medical charts, we extracted clinical information for 384 patients infected with the Omicron variant in Anyang City, Henan Province, China. Epidemiology and clinical characteristics were compared with a cohort of people infected with the Delta variant in Zhengzhou in 2021. Findings: Common initial symptoms at onset of illness were cough [240 (63%)], expectoration [112 (29%)], fever [96 (25%)], nasal congestion [96 (25%)] and myalgia or fatigue [30 (6%)]. In patients with the Omicron variant, levels of total cholesterol, low-density lipoprotein and creatinine increased in 52 (14%), 36 (9%) and 58 (15%) patients, respectively, compared with patients with the Delta variant [one (1%), one (1%) and two (2%)]. Levels of triglyceride and high-density lipoprotein also increased. In patients with the Omicron variant, the levels of specific gravity and the erythrocyte sedimentation rate were increased in 115 (30%) and 81 (21%) patients, and serum levels of complement 3 decreased in 93 (41%). Results: Compared with patients infected with Delta, no major differences in initial clinical symptoms were identified in patients infected with Omicron. However, dyslipidemia and kidney injury were much more severe in patients with the Omicron variant, and the erythrocyte sedimentation rate was increased. Due to decreased levels of complement 3, the immunity of patients with the Omicron variant was weak.

Comparison of clinical characteristics between SARS-CoV-2 Omicron variant and Delta variant infections in China

Background The continued ‘evolution’ of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of the Omicron variant after the Delta variant, resulting in a significant increase in the number of people with COVID-19. This increase in the number of cases continues to have a significant impact on lives. Therefore, a more detailed understanding of the clinical characteristics of Omicron infection is essential. Methods Using medical charts, we extracted clinical information for 384 patients infected with the Omicron variant in Anyang City, Henan Province, China. Epidemiology and clinical characteristics were compared with a cohort of people infected with the Delta variant in Zhengzhou in 2021. Findings Common initial symptoms at onset of illness were cough [240 (63%)], expectoration [112 (29%)], fever [96 (25%)], nasal congestion [96 (25%)] and myalgia or fatigue [30 (6%)]. In patients with the Omicron variant, levels of total cholesterol, low-density lipoprotein and creatinine increased in 52 (14%), 36 (9%) and 58 (15%) patients, respectively, compared with patients with the Delta variant [one (1%), one (1%) and two (2%)]. Levels of triglyceride and high-density lipoprotein also increased. In patients with the Omicron variant, the levels of specific gravity and the erythrocyte sedimentation rate were increased in 115 (30%) and 81 (21%) patients, and serum levels of complement 3 decreased in 93 (41%). Results Compared with patients infected with Delta, no major differences in initial clinical symptoms were identified in patients infected with Omicron. However, dyslipidemia and kidney injury were much more severe in patients with the Omicron variant, and the erythrocyte sedimentation rate was increased. Due to decreased levels of complement 3, the immunity of patients with the Omicron variant was weak.

Effectiveness Evaluation of a Primary School-Based Intervention against Heatwaves in China.

BACKGROUND: Evidence of the effectiveness of intervention against extreme heat remains unclear, especially among children, one of the vulnerable populations. This study aimed to evaluate the effectiveness of a primary school-based intervention program against heatwave and climate change in China to provide evidence for development of policies for adaptation to climate change. METHODS: Two primary schools in Dongtai City, Jiangsu Province, China, were randomly selected as intervention and control schools (CTR registration number: ChiCTR2200056005). Health education was conducted at the intervention school to raise students' awareness and capability to respond to extreme heat during May to September in 2017. Knowledge, attitude, and practice (KAP) of students and their parents at both schools were investigated by questionnaire surveys before and after intervention. The changes in KAP scores after intervention were evaluated using multivariable difference-in-difference (DID) analysis, controlling for age, sex, etc. Results: The scores of knowledge, attitude, and practice of students and their parents increased by 19.9% (95%CI: 16.3%, 23.6%) and 22.5% (95%CI: 17.8%, 27.1%); 9.60% (95%CI: 5.35%, 13.9%) and 7.22% (95%CI: 0.96%, 13.5%); and 9.94% (95%CI: 8.26%, 18.3%) and 5.22% (95%CI: 0.73%, 9.71%), respectively, after intervention. The KAP score changes of boys were slightly higher than those of girls. Older students had higher score changes than younger students. For parents, the higher the education level, the greater the score change, and change in scores was greater in females than in males. All the health education activities in the program were significantly correlated with the changes in KAP scores of primary school students after intervention, especially those curricula with interesting activities and experiential learning approaches. CONCLUSIONS: Heat and health education program in primary school was an effective approach to improve cognition and behavior for both students and their parents to better adapt to heatwaves and climate change. The successful experience can be generalized to respond to the increasing extreme weather/climate events in the context of climate change, such as heatwaves, and other emergent occasions or public health education, such as the control and prevention of COVID-19.

Comparison of the community-acquired pneumonia and COVID-19 at the early stage: findings from two cohort studies.

BACKGROUND: The current focus is largely on whole course medical management of coronavirus disease-19 (COVID-19) with real-time polymerase chain reaction (RT-PCR) and radiological features, while the mild cases are usually missed. Thus, combination of multiple diagnostic methods is urgent to understand COVID-19 fully and to monitor the progression of COVID-19. METHODS: laboratory variables of 40 mild COVID-19 patients, 30 patients with community-acquired pneumonia (CAP) and 32 healthy individuals were analyzed by principal component analysis (PCA), Kruskal test, Procrustes test, the vegan package in R, CCA package and receiver operating characteristic to investigate the characteristics of the laboratory variables and their relationships in COVID-19. RESULTS: The correlations between the laboratory variables presented a variety of intricate linkages in the COVID-19 group compared with the healthy group and CAP patient group. The prediction probability of the combination of lymphocyte count (LY), eosinophil (EO) and platelets (PLT) was 0.847, 0.854 for the combination of lactate (LDH), creatine kinase isoenzyme (CK-MB), and C-reactive protein (CRP), 0.740 for the combination of EO, white blood cell count (WBC) and neutrophil count (NEUT) and 0.872 for the combination of CK-MB and P. CONCLUSIONS: The correlations between the laboratory variables in the COVID-19 group could be a unique characteristic showing promise as a method for COVID-19 prediction and monitoring progression of COVID-19 infection.

Comparison of ARIMA and LSTM in Forecasting the Incidence of HFMD Combined and Uncombined with Exogenous Meteorological Variables in Ningbo, China.

BACKGROUND: This study intends to identify the best model for predicting the incidence of hand, foot and mouth disease (HFMD) in Ningbo by comparing Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory Neural Network (LSTM) models combined and uncombined with exogenous meteorological variables. METHODS: The data of daily HFMD incidence in Ningbo from January 2014 to November 2017 were set as the training set, and the data of December 2017 were set as the test set. ARIMA and LSTM models combined and uncombined with exogenous meteorological variables were adopted to fit the daily incidence of HFMD by using the data of the training set. The forecasting performances of the four fitted models were verified by using the data of the test set. Root mean square error (RMSE) was selected as the main measure to evaluate the performance of the models. RESULTS: The RMSE for multivariate LSTM, univariate LSTM, ARIMA and ARIMAX (Autoregressive Integrated Moving Average Model with Exogenous Input Variables) was 10.78, 11.20, 12.43 and 14.73, respectively. The LSTM model with exogenous meteorological variables has the best performance among the four models and meteorological variables can increase the prediction accuracy of LSTM model. For the ARIMA model, exogenous meteorological variables did not increase the prediction accuracy but became the interference factor of the model. CONCLUSIONS: Multivariate LSTM is the best among the four models to fit the daily incidence of HFMD in Ningbo. It can provide a scientific method to build the HFMD early warning system and the methodology can also be applied to other communicable diseases.

Assessment of the Association of Vitamin D Level With SARS-CoV-2 Seropositivity Among Working-Age Adults.

Importance: Low vitamin D levels have been reported to be associated with increased risk of SARS-CoV-2 infection. Independent, well-powered studies could further our understanding of this association. Objective: To examine whether low levels of vitamin D are associated with SARS-CoV-2 seropositivity, an indicator of previous infection. Design, Setting, and Participants: This is a cohort study of employees and spouses who elected to be tested for SARS-CoV-2 IgG as part of an annual employer-sponsored health screening program conducted in August to November 2020. This program includes commonly assessed demographic, biometric, and laboratory variables, including total vitamin D measurement. Baseline (prepandemic) levels of vitamin D and potential confounders were obtained from screening results from the previous year (September 2019 to January 2020). Data analysis was performed from December 2020 to March 2021. Exposures: Low total serum 25-hydroxyvitamin D, defined as either less than 20 ng/mL or less than 30 ng/mL. Main Outcomes and Measures: The main outcome was SARS-CoV-2 seropositivity, as determined with US Food and Drug Administration emergency use-authorized assays. The association of SARS-CoV-2 seropositivity with vitamin D levels was assessed by multivariable logistic regression analyses and propensity score analyses. Results: The 18 148 individuals included in this study had test results for SARS-CoV-2 IgG in 2020 and vitamin D levels from the prepandemic and pandemic periods. Their median (interquartile range) age was 47 (37-56) years, 12 170 (67.1%) were women, 900 (5.0%) were seropositive, 4498 (24.8%) had a vitamin D level less than 20 ng/mL, and 10 876 (59.9%) had a vitamin D level less than 30 ng/mL before the pandemic. In multivariable models adjusting for age, sex, race/ethnicity, education, body mass index, blood pressure, smoking status, and geographical location, SARS-CoV-2 seropositivity was not associated with having a vitamin D level less than 20 ng/mL before (odds ratio [OR], 1.04; 95% CI, 0.88-1.22) or during (OR, 0.93; 95% CI, 0.79-1.09) the pandemic; it was also not associated with having a vitamin D level less than 30 ng/mL before (OR, 1.09; 95% CI, 0.93-1.27) or during (OR, 1.05; 95% CI, 0.91-1.23) the pandemic. Similar results were observed in propensity score analyses. SARS-CoV-2 seropositivity was associated with obesity (OR, 1.26; 95% CI, 1.08-1.46), not having a college degree (OR, 1.40; 95% CI, 1.21-1.62), and Asian (OR, 1.46; 95% CI, 1.13-1.87), Black (OR, 2.74; 95% CI, 2.25-3.34), Hispanic (OR, 2.65; 95% CI, 2.15-3.27), American Indian or Alaska Native, and Native Hawaiian or other Pacific Islander (OR, 2.01; OR, 1.54-2.62) race/ethnicity, and was inversely associated with high blood pressure (OR, 0.82; 95% CI, 0.70-0.96), smoking (OR, 0.60; 95% CI, 0.47-0.78), and residing in the US Northeast (OR, 0.75; 95% CI, 0.62-0.92) and West (OR, 0.54; 95% CI, 0.44-0.67). Conclusions and Relevance: In this cohort study, SARS-CoV-2 seropositivity was not associated with low levels of vitamin D independently of other risk factors.

Impact of the COVID-19 epidemic on patterns of pregnant women's perception of threat and its relationship to mental state: A latent class analysis.

OBJECTIVE: The objective of this study was to define the threatened perception types of pregnant women during the COVID-19 pandemic and determine the correlations between the perception types and their demographic factors, their preventive knowledge of COVID-19 and their mental status in order to provide suggestions for pregnant women during pandemic. METHODS: Latent class analysis were used to explore the optimal numbers of clusters. Multinomial logistic regression and multiple correspondence analysis were used to analyze the demographic variables of the latent categories. MANOVA was used to analyze the difference of knowledge of COVID-19 obtained among clusters and their psychological status, and chi-square test was used determine the relationship between the latent clusters and the participant's COVID-19 worry level. RESULTS: Five clusters were found: the first cluster (n = 120, 39%) was unthreatened and confident. Cluster 2(n = 84, 28%) was unthreatened but not confident. Cluster 3 (n = 49, 17%) was threatened but confident. Cluster 4 (n = 25, 9%) was threaten, not confident and knowledgeable, and Cluster 5 (n = 20, 7%) was threatened, not confident and lacking knowledge. Three demographic variables were shown an effect on the classification, they were support from work, family support and intrapartum and postpartum complications. CONCLUSION: This study can help assess the mental health risks of pregnant women during an epidemic. The results could be helpful for families, work units, communities and medical institutions to make targeted intervention decisions for pregnant women.