Successful detection of SARS-COV-2 in wastewater suggests the potential utility of wastewater-based epidemiology (WBE) for COVID-19 community surveillance. This systematic review aims to assess the performance of wastewater surveillance as early warning system of COVID-19 community transmission. A systematic search was conducted in PubMed, Medline, Embase and the WBE Consortium Registry according to PRISMA guidelines for relevant articles published until 31st July 2021. Relevant data were extracted and summarized. Quality of each paper was assessed using an assessment tool adapted from Bilotta et al.'s tool for environmental science. Of 763 studies identified, 92 studies distributed across 34 countries were shortlisted for qualitative synthesis. A total of 26,197 samples were collected between January 2020 and May 2021 from various locations serving population ranging from 321 to 11,400,000 inhabitants. Overall sample positivity was moderate at 29.2% in all examined settings with the spike (S) gene having maximum rate of positive detections and nucleocapsid (N) gene being the most targeted. Wastewater signals preceded confirmed cases by up to 63 days, with 13 studies reporting sample positivity before the first cases were detected in the community. At least 50 studies reported an association of viral load with community cases. While wastewater surveillance cannot replace large-scale diagnostic testing, it can complement clinical surveillance by providing early signs of potential transmission for more active public health responses. However, more studies using standardized and validated methods are required along with risk analysis and modelling to understand the dynamics of viral outbreaks.

Background: On 29th December 2019, a cluster of cases displaying the symptoms of a "pneumonia of unknown cause" was identified in Wuhan, Hubei province of China. This systematic review and meta-analysis aims to review the epidemiological and clinical characteristics of COVID-19 cases in the early phase of the COVID-19 pandemic. Methods: The search strategy involved peer-reviewed studies published between 1st January and 11th February 2020 in Pubmed, Google scholar and China Knowledge Resource Integrated database. Publications identified were screened for their title and abstracts according to the eligibility criteria, and further shortlisted by full-text screening. Three independent reviewers extracted data from these studies, and studies were assessed for potential risk of bias. Studies comprising non-overlapping patient populations, were included for qualitative and quantitative synthesis of results. Pooled prevalence with 95% confidence intervals were calculated for patient characteristics. Results: A total of 29 publications were selected after full-text review. This comprised of 18 case reports, three case series and eight cross-sectional studies on patients admitted from mid-December of 2019 to early February of 2020. A total of 533 adult patients with pooled median age of 56 (95% CI: 49-57) and a pooled prevalence of male of 60% (95% CI: 52-68%) were admitted to hospital at a pooled median of 7 days (95% CI: 7-7) post-onset of symptoms. The most common symptoms at admission were fever, cough and fatigue, with a pooled prevalence of 90% (95% CI: 81-97%), 58% (95% CI: 47-68%), and 50% (95% CI: 29-71%), respectively. Myalgia, shortness of breath, headache, diarrhea and sore throat were less common with pooled prevalence of 27% (95% CI: 20-36%), 25% (95% CI: 15-35%), 10% (95% CI: 7-13%), 8% (95% CI: 5-13%), and 7% (95% CI: 1-15%), respectively. ICU patients had a higher proportion of shortness of breath at Koh et al. Epidemiological and Clinical Features of COVID-19 Cases presentation, as well as pre-existing hypertension, cardiovascular disease and COPD, compared to non-ICU patients in 2 studies (n = 179). Conclusion: This study highlights the key epidemiological and clinical features of COVID-19 cases during the early phase of the COVID-19 pandemic.

This systematic and meta-review aimed to compare clinical presentation, outcomes, and care management among patients with COVID-19 during the early phase of the pandemic. A total of 77 peer-reviewed publications were identified between January 1, 2020 and April 9, 2020 from PubMed, Google Scholar, and Chinese Medical Journal databases. Subsequently, meta-analysis of 40 non-overlapping studies, comprising of 4844 patients from seven countries, was conducted to see differences in clinical characteristics and laboratory outcomes across patients from different geographical regions (Wuhan, other parts of China and outside China), severity (non-severe, severe and fatal) and age groups (adults and children). Patients from Wuhan had a higher mean age (54.3 years) and rates of dyspnea (39.5%) compared with patients from other parts of China and outside China. Myalgia, fatigue, acute respiratory distress syndrome (ARDS) and fatalities were also significantly more prevalent among Wuhan patients. A significant dose–response increase in prevalence of diabetes, D-dimer, white blood cells, neutrophil levels and ARDS was seen from non-severe to severe and fatal outcomes. A significant increase in mean duration of symptom onset to admission was seen between non-severe cases (4.2 days) and severe and fatal cases (6.3 days and 8.8 days, respectively). Proportion of asymptomatic cases was higher in children (20%) compared with adults (2.4%). In conclusion, patients with COVID-19 from Wuhan displayed more severe clinical disease during the early phase of the pandemic, while disease severity was significantly lesser among pediatric cases. This review suggests that biomarkers at admission may be useful for prognosis among patients with COVID-19.

BackgroundAcute respiratory infections (ARI), including the common cold causes significant morbidity and economical losses globally. Micronutrient deficiency may increase ARI incidence risk and its associated duration and severity among healthy adults, but evidence are inconclusive. This study aims to systematically review all observations on the association between single micronutrient deficiency and ARI incidence, duration and severity in healthy adults.MethodsSystematic literature searches were conducted in PubMed, Cochrane Library, Embase and Scopus databases. Eligible studies were assessed for the reporting and methodological quality. Adjusted summary statistics with their relevant 95% confidence intervals or interquartile ranges were extracted for the outcomes of interest.ResultsThe literature search identified 423 unique studies. Of which, only eight studies were eligible and included in the final review. Only vitamin D deficiency (VDD) was observed among these eight studies. There were no eligible studies that focused on the association between other single micronutrient deficiency and ARI. The review found mixed observations on ARI incidence, and a lack of evidence on its associated severity to conclude the association between VDD and these outcomes. However, existing evidence consistently suggested that VDD is likely to lead to longer ARI duration (median duration in days: deficient group, 4 to 13; non-deficient groups, 2 to 8).ConclusionThis review found that VDD may be associated to longer ARI duration, but its effect on ARI incidence and its associated severity among healthy adults remains inconclusive. This review also highlighted the lack of a consistent regional and/or global definition for micronutrient sufficiency, and that future studies should explore and conclude the association between other micronutrient deficiency and ARIs in healthy adults before considering supplementation for ARI prevention and management.

This study assessed the impact of weather factors, including novel predictors—pollutant standards index (PSI) and wind speed—on dengue incidence in Singapore between 2012 and 2019. Autoregressive integrated moving average (ARIMA) model was fitted to explore the autocorrelation in time series and quasi-Poisson model with a distributed lag non-linear term (DLNM) was set up to assess any non-linear association between climatic factors and dengue incidence. In DLNM, a PSI level of up to 111 was positively associated with dengue incidence; incidence reduced as PSI level increased to 160. A slight rainfall increase of up to 7 mm per week gave rise to higher dengue risk. On the contrary, heavier rainfall was protective against dengue. An increase in mean temperature under around 28.0 °C corresponded with increased dengue cases whereas the association became negative beyond 28.0 °C; the minimum temperature was significantly positively associated with dengue incidence at around 23–25 °C, and the relationship reversed when temperature exceed 27 °C. An overall positive association, albeit insignificant, was observed between maximum temperature and dengue incidence. Wind speed was associated with decreasing relative risk (RR). Beyond prevailing conclusions on temperature, this study observed that extremely poor air quality, high wind speed, minimum temperature ≥27 °C, and rainfall volume beyond 12 mm per week reduced the risk of dengue transmission in an urbanized tropical environment.

Background: The rapid spread of the COVID-19 pandemic demonstrates the value of regional cooperation in infectious disease prevention and control. We explored the literature on regional infectious disease control bodies, to identify lessons, barriers and enablers to inform operationalisation of a regional infectious disease control body or network in southeast Asia. Methods: We conducted a scoping review to examine existing literature on regional infectious disease control bodies and networks, and to identify lessons that can be learned that will be useful for operationalisation of a regional infectious disease control body such as the ASEAN Center for Public Health Emergency and Emerging Diseases. Results: Of the 57 articles included, 53 (93%) were in English, with two (3%) in Spanish and one (2%) each in Dutch and French. Most were commentaries or review articles describing programme initiatives. Sixteen (28%) publications focused on organisations in the Asian continent, with 14 (25%) focused on Africa, and 14 (24%) primarily focused on the European region. Key lessons focused on organisational factors, diagnosis and detection, human resources, communication, accreditation, funding, and sustainability. Enablers and constraints were consistent across regions/organisations. A clear understanding of the regional context, budgets, cultural or language issues, staffing capacity and governmental priorities, is pivotal. An initial workshop inclusive of the various bodies involved in the design, implementation, monitoring or evaluation of programmes is essential. Clear governance structure, with individual responsibilities clear from the beginning, will reduce friction. Secure, long-term funding is also a key aspect of the success of any programme. Conclusion: Operationalisation of regional infectious disease bodies and networks is complicated, but with extensive groundwork, and focus on organisational factors, diagnosis and detection, human resources, communication, accreditation, funding, and sustainability, it is achievable. Ways to promote success are to include as many stakeholders as possible from the beginning, to ensure that context-specific factors are considered, and to encourage employees through capacity building and mentoring, to ensure they feel valued and reduce staff turnover.

BackgroundThe association of weather factors on dengue transmission in an urbanized tropical environment remains inconclusive. This study aims to assess the impact of weather factors on dengue incidence in Singapore between 2012 and 2019.MethodsData on weather variables (daily temperature, air quality, rainfall & wind speed) and weekly dengue incidence rates were collected from 1 January 2012 to 25 August 2019. Statistically significant correlated variables identified from cross-correlation analysis using Pearson’s correlation were examined in univariate ARIMA model. A distributed lag non-linear model (DLNM) with Quasi-Poisson model was established to assess any non-linear association between climatic factors and dengue incidence. The Quasi-Poisson model coefficients were evaluated using Quasi Akaike’s Information Criterion (QAIC). To validate the model, the data was split into testing and validation sets, with QAIC, Mean Absolute Error (MAE) & Root Mean Square Error (RMSE) reported. ResultsPollutant Standards Indices (PSI) greater than 100 was associated to lower weekly dengue incidence at a 5-week and a 7-week lag period. High wind speeds at 5-week lag time was also associated with reduced dengue transmission. Mean and minimum temperatures of 28℃ and 25℃ respectively were associated with reduced risk of weekly dengue transmission across all lags effect. Mean temperatures above 28℃ at a 1-week lag and maximum temperatures above 32℃ at an 11-week lag promoted dengue transmission. Rainfall was not correlated with dengue cases in Singapore.Based on split-sample model validation, mean temperature was the best predictor of dengue (MAE: 43.15, RMSE: 51.39). Weather factors had varied influence on both pre-epidemic surge periods and non-epidemic periods, but had a stronger correlation with dengue transmission in non-epidemic periods. ConclusionsPoor air quality and high wind speeds were associated with reduced risk of dengue transmission in an urbanized tropical environment. Only a limited temperature range promotes dengue transmission.

IntroductionThe association of weather factors on dengue transmission in an urbanized tropical environment remains inconclusive. This study aims to assess the impact of weather factors on dengue incidence in Singapore between 2012 and 2019.MethodsData on weather variables (daily temperature, air quality, rainfall & wind speed) and weekly dengue incidence rates were collected from 1 January 2012 to 25 August 2019. Statistically significant correlated variables identified from cross-correlation analysis using Pearson’s correlation were examined in univariate ARIMA model. Quasi-Poisson model with a distributed lag non-linear model (DLNM) was established to assess any non-linear association between climatic factors and dengue incidence. FindingsPoor air quality (PSI: 150) and high wind speeds (12 km/h) were associated with reduced risk of dengue transmission in an urbanized tropical environment. Only a limited temperature range (27-32 °C and 23-25 °C) promotes dengue transmission whereas extreme heat inhibited dengue incidence (27°C, Ref. 25.14 °C; RR: 0.74, 95% CI: 0.58, 0.93). Rainfall exerts positive and negative influence alternately on weekly dengue cases across lags but the influence was not robust in sensitivity analysis. Based on split-sample model validation, mean temperature was the best predictor of dengue in prediction part (MAE: 43.15, RMSE: 51.39).