Prevalence & Impact of COVID-19 in Systemic Sclerosis Patients and Assessment of the Demographic & Clinical Features in Cases Associated with Worse Prognosis: Results of a Single Centre Registry.

Background: Our knowledge of the COVID-19 infection impact on systemic sclerosis (SSc) is scarce. This study aimed to assess the prevalence of COVID-19 infection and to determine the predictive factors of worse outcomes and death in SSc patients. Methods: In this cohort study all patients who attended our clinic between 20th February 2020 and 20th May 2021 were followed, and those with a history of COVID-19 infection completed the questionnaire. Results of para-clinical tests were extracted from the SSc database. The outcomes were classified as: alive vs. deceased and, mild vs. worse outcomes. Descriptive statistics and binary logistic regression models were applied. Results: Of the total 192 SSc patients studied, COVID-19 affected 12.5%; 6% experienced mild disease, 7% were hospitalized and 3% died. The worse outcome was associated with: older age [95%CI: 1.00-1.08], smoking [95%CI: 2.632-33.094], diabetes [95%CI: 1.462-29.654], digital pitting scars (DPS) [95%CI: 1.589-21.409], diffusing capacity of the lungs for carbon monoxide [DLCO<70 [95%CI: 1.078-11.496], left ventricular ejection fraction (LVEF)<50% [95%CI: 1.080-38.651], systolic pulmonary artery pressure (sPAP)>40 mmHg [95%CI: 1.332-17.434], pericardial effusion (PE) [95%CI: 1.778-39.206], and tendon friction rub [95%CI: 1.091-9.387]. Death was associated with male gender [95%CI: 1.54-88.04], hypertension [95%CI: 1.093-2.155], digital ulcers (DU) [95%CI: 0.976-18.34], low forced vital capacity (FVC) [95%CI: 0.03-0.81], and joint flexion contracture (JFC) [95%CI: 1.226-84.402]. Conclusion: Risk factors for the worse outcome in COVID-19 infected SSc patients included, older age, smoking, diabetes, DPS, DLCO<70, LVEF<50%, sPAP>40 mmHg, PE, and TFR. Death was associated with the male gender, hypertension, DU, low FVC, and JFC.

Low prevalence of SARS-CoV-2 among patients presenting at a Parisian psychiatry University Hospital Group

Abstract: We examine the prevalence of SARS-CoV-2 infections among patients admitted to a Parisian psychiatric University Hospital Group (GHU).A total of 548 patients were admitted to the GHU...s full-time psychiatric wards between April 6 and May 3 2020. More than 80% were tested. A total of 7 patients tested positive for the SARS-Cov-2 (1.3%), with 5 patients (in 92, 5.4%) testing positive in the first week.GHU patients presented a low prevalence of SARS-CoV-2, even if all patients live in the hardest hit region in France. Social isolation and loneliness, as well as self-isolation of patients with symptoms could explain our results. (AU)

Low prevalence of SARS-CoV-2 among patients presenting at a Parisian psychiatry University Hospital Group.

We examine the prevalence of SARS-CoV-2 infections among patients admitted to a Parisian psychiatric University Hospital Group (GHU). A total of 548 patients were admitted to the GHU...s full-time psychiatric wards between April 6 and May 3 2020. More than 80% were tested. A total of 7 patients tested positive for the SARS-Cov-2 (1.3%), with 5 patients (in 92, 5.4%) testing positive in the first week. GHU patients presented a low prevalence of SARS-CoV-2, even if all patients live in the hardest hit region in France. Social isolation and loneliness, as well as self-isolation of patients with symptoms could explain our results.

Trajectories of parent and child well-being across the pandemic year: Role of financial strain, social distancing, and COVID-19 prevalence.

Existing research demonstrated large deteriorations in parent, child, and family well-being within 2 months after the onset of the COVID-19 pandemic. Yet, little is known about the trajectories of families' adjustment in the following months, including what risk factors are associated with changes in families' adjustment. The current study examined (1) change in the parent, child, and family well-being over time; (2) associations of pandemic-related stressors, financial and social distancing-associated stress, with well-being between and within families; and (3) the role of local COVID-19 prevalence, prior participation in family-focused prevention, and parent gender. From April 2020 to January 2021, 393 parents from 235 families reported five times on parent mental health, child behavior problems, family relationships, and pandemic-related stressors. Findings indicate that, across all domains of well-being, there was either little change across the 8 months or a small degree of recovery followed by a shift to further deterioration. On average, parents experiencing greater pandemic-related stressors also reported poorer functioning in all domains; monthly fluctuations in pandemic-related stressors were also associated with fluctuations in parent mental health and child behavior problems. In some domains, the links between pandemic-related stressors and parent and child well-being were stronger among families living in areas with overall higher COVID-19 prevalence rates. Parents' experiences during the pandemic did not differ systematically across prior intervention participation or parent gender. Taken together, findings suggest a need for supportive interventions to help families navigate extended periods of crisis.

Association between multimorbidity, intensive care unit admission, and death in patients with COVID-19 in Brazil: a cross-section study, 2020

ABSTRACT BACKGROUND: Multimorbidity can influence intensive care unit (ICU) admissions and deaths due to coronavirus disease (COVID-19). OBJECTIVE: To analyze the association between multimorbidity, ICU admissions, and deaths due to COVID-19 in Brazil. DESIGN AND SETTING: This cross-sectional study was conducted using data from patients with severe acute respiratory syndrome (SARS) due to COVID-19 recorded in the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) in 2020. METHODS: Descriptive and stratified analyses of multimorbidity were performed based on sociodemographic, ventilatory support, and diagnostic variables. Poisson regression was used to estimate the prevalence ratios. RESULTS: We identified 671,593 cases of SARS caused by COVID-19, of which 62.4% had at least one morbidity. Multimorbidity was associated with male sex, age 60-70 and ≥ 80 years, brown and black skin color, elementary education and high school, ventilatory support, and altered radiologic exams. Moreover, all regions of the country and altered computed tomography due to COVID-19 or other diseases were associated with death; only the northeast region and higher education were associated with ICU admission. CONCLUSION: Our results showed an association between multimorbidity, ICU admission, and death in COVID-19 patients in Brazil.

The Importance of Incorporating At-Home Testing Into SARS-CoV-2 Point Prevalence Estimates: Findings From a US National Cohort, February 2022.

BACKGROUND: Passive, case-based surveillance underestimates the true extent of active infections in the population due to undiagnosed and untested cases, the exclusion of probable cases diagnosed point-of-care rapid antigen tests, and the exclusive use of at-home rapid tests which are not reported as part of case-based surveillance. The extent in which COVID-19 surveillance may be underestimating the burden of infection is likely due to time-varying factors such as decreased test-seeking behaviors and increased access to and availability of at-home testing. OBJECTIVE: The objective of this study is to estimate the prevalence of SARS-CoV-2 based on different definitions of a case to ascertain the extent to which cases of SARS-CoV-2 may be underestimated by case-based surveillance. METHODS: A survey on COVID-19 exposure, infection, and testing was administered to calculate point prevalence of SARS-CoV-2 among a diverse sample of cohort adults from February 8, 2022, to February 22, 2022. Three-point prevalence estimates were calculated among the cohort, as follows: (1) proportion positives based on polymerase chain reaction (PCR) and rapid antigen tests; (2) proportion positives based on testing exclusively with rapid at-home tests; and (3) proportion of probable undiagnosed cases. Test positivity and prevalence differences across booster status were also examined. RESULTS: Among a cohort of 4328, there were a total of 644 (14.9%) cases. The point prevalence estimate based on PCR or rapid antigen tests was 5.5% (95% CI 4.8%-6.2%), 3.7% (95% CI 3.1%-4.2%) based on at-home rapid tests, and 5.7% (95% CI 5.0%-6.4%) based on the case definition of a probable case. The total point prevalence across all definitions was 14.9% (95% CI 13.8%-16.0%). The percent positivity among PCR or rapid tests was 50.2%. No statistically significant differences were observed in prevalence between participants with a COVID-19 booster compared to fully vaccinated and nonboosted participants except among exclusive at-home rapid testers. CONCLUSIONS: Our findings suggest a substantial number of cases were missed by case-based surveillance systems during the Omicron B.1.1.529 surge, when at-home testing was common. Point prevalence surveys may be a rapid tool to be used to understand SARS-CoV-2 prevalence and would be especially important during case surges to measure the scope and spread of active infections in the population.

Prevalence of Coronavirus Disease 2019 (COVID-19) in Different Clinical Stages before the National COVID-19 Vaccination Programme in Malaysia: A Systematic Review and Meta-Analysis.

More than 1.75 million COVID-19 infections and 16 thousand associated deaths have been reported in Malaysia. A meta-analysis on the prevalence of COVID-19 in different clinical stages before the National COVID-19 Vaccination Program in Malaysia is still lacking. To address this, the disease severity of a total of 215 admitted COVID-19 patients was initially recorded in the early phase of this study, and the data were later pooled into a meta-analysis with the aim of providing insight into the prevalence of COVID-19 in 5 different clinical stages during the outset of the COVID-19 pandemic in Malaysia. We have conducted a systematic literature search using PubMed, Web of Science, Scopus, ScienceDirect, and two preprint databases (bioRxiv and medRxiv) for relevant studies with specified inclusion and exclusion criteria. The quality assessment for the included studies was performed using the Newcastle-Ottawa Scale. The heterogeneity was examined with an I2 index and a Q-test. Funnel plots and Egger's tests were performed to determine publication bias in this meta-analysis. Overall, 5 studies with 6375 patients were included, and the pooled prevalence rates in this meta-analysis were calculated using a random-effect model. The highest prevalence of COVID-19 in Malaysia was observed in Stage 2 cases (32.0%), followed by Stage 1 (27.8%), Stage 3 (17.1%), Stage 4 (7.6%), and Stage 5 (3.4%). About two-thirds of the number of cases have at least one morbidity, with the highest percentage of hypertension (66.7%), obesity (55.5%), or diabetes mellitus (33.3%) in Stage 5 patients. In conclusion, this meta-analysis suggested a high prevalence of COVID-19 occurred in Stage 2. The prevalence rate in Stage 5 appeared to be the lowest among COVID-19 patients before implementing the vaccination program in Malaysia. These meta-analysis data are critically useful for designing screening and vaccination programs and improving disease management in the country.

SARS-CoV-2 serosurvey among adults involved in healthcare and health research in Guinea-Bissau, West Africa.

OBJECTIVES: Many African countries have reported fewer COVID-19 cases than countries elsewhere. By the end of 2020, Guinea-Bissau, West Africa, had <2500 PCR-confirmed cases corresponding to 0.1% of the ∼1.8 million national population. We assessed the prevalence of SARS-CoV-2 antibodies in urban Guinea-Bissau to help guide the pandemic response in Guinea-Bissau. STUDY DESIGN: Cross-sectional assessment of SARS-CoV-2 antibody in a cohort of staff at the Bandim Health Project. METHODS: We measured IgG antibodies using point-of-care rapid tests among 140 staff and associates at a biometric research field station in Bissau, the capital of Guinea-Bissau, during November 2020. RESULTS: Of 140 participants, 25 (18%) were IgG-positive. Among IgG-positives, 12 (48%) reported an episode of illness since the onset of the pandemic. Twenty-five (18%) participants had been PCR-tested between May and September; 7 (28%) had been PCR-positive. Four of these seven tested IgG-negative in the present study. Five participants reported that somebody had died in their house, corresponding crudely to an annual death rate of 4.5/1000 people; no death was attributed to COVID-19. Outdoor workers had a lower prevalence of IgG-positivity. CONCLUSIONS: In spite of the low official number of COVID-19 cases, our serosurvey found a high prevalence of IgG-positivity. Most IgG-positives had not been ill. The official number of PCR-confirmed COVID-19 cases has thus grossly underestimated the prevalence of COVID-19 during the pandemic. The observed overall mortality rate in households of Bandim Health Project employees was not higher than the official Guinean mortality rate of 9.6/1000 people.

Wastewater, waste, and water-based epidemiology (WWW-BE): A novel hypothesis and decision-support tool to unravel COVID-19 in low-income settings?

Traditional wastewater-based epidemiology (W-BE) relying on SARS-CoV-2 RNA detection in wastewater is attractive for understanding COVID-19. Yet traditional W-BE based on centralized wastewaters excludes putative SARS-CoV-2 reservoirs such as: (i) wastewaters from shared on-site sanitation facilities, (ii) solid waste including faecal sludge from non-flushing on-site sanitation systems, and COVID-19 personal protective equipment (PPE), (iii) raw/untreated water, and (iv) drinking water supply systems in low-income countries (LICs). A novel hypothesis and decision-support tool based on Wastewater (on-site sanitation, municipal sewer systems), solid Waste, and raw/untreated and drinking Water-based epidemiology (WWW-BE) is proposed for understanding COVID-19 in LICs. The WWW-BE conceptual framework, including components and principles is presented. Evidence on the presence of SARS-CoV-2 and its proxies in wastewaters, solid materials/waste (papers, metals, fabric, plastics), and raw/untreated surface water, groundwater and drinking water is discussed. Taken together, wastewaters from municipal sewer and on-site sanitation systems, solid waste such as faecal sludge and COVID-19 PPE, raw/untreated surface water and groundwater, and drinking water systems in LICs act as potential reservoirs that receive and harbour SARS-CoV-2, and then transmit it to humans. Hence, WWW-BE could serve a dual function in estimating the prevalence and potential transmission of COVID-19. Several applications of WWW-BE as a hypothesis and decision support tool in LICs are discussed. WWW-BE aggregates data from various infected persons in a spatial unit, hence, putatively requires less resources (analytical kits, personnel) than individual diagnostic testing, making it an ideal decision-support tool for LICs. The novelty, and a critique of WWW-BE versus traditional W-BE are presented. Potential challenges of WWW-BE include: (i) biohazards and biosafety risks, (ii) lack of expertise, analytical equipment, and accredited laboratories, and (iii) high uncertainties in estimates of COVID-19 cases. Future perspectives and research directions including key knowledge gaps and the application of novel and emerging technologies in WWW-BE are discussed.

Prevalence and associated factors for kidney dysfunction in hospitalized patients with COVID-19 pneumonia in Zambia

Abstract Background: A significant link has been reported between COVID-19 pneumonia, disease severity and development of kidney dysfunction. This study assessed the prevalence and correlated factors for kidney impairment in hospitalized patients with COVID-19 infection Methods: This nested retrospective study examined medical files of patients with confirmed COVID-19 pneumonia. The outcome variable was kidney dysfunction ( defined as functional renal indexes beyond the normal range) and associated factors. Multivariate logistic regression was employed to establish factors associated with renal dysfunction. Results: 179 patients were included in this nested study and the mean age was 58.3 years (SD 16.5) and 49.0% were female. The prevalence of renal dysfunction was 51.9% and 39.3% these patients renal had eGFR<60 mL/min/1.73m2 The proportion of kidney impairment was higher in males than females (59.3% vs.44.3 %), patients with underlying hypertension than normotensive (60.5% vs. 39.5 %) and those with chronic kidney disease (CKD) than those without (90% vs. 10%). After adjusting for age, male gender, critical COVID-19 disease, and raised white cell count, hypertension was an independent predictor of kidney impairment with a AOR 1.54 (95% CI [1.06-2.23],p=0.022). Presence of HIV or diabetes mellitus showed a non statistical significance with renal dysfunction. Conclusion: The study demonstrated a high prevalence of kidney dysfunction in hospitalized patients with COVID-19 pneumonia and presence of hypertension predicted nearly 2-fold development renal impairment.

Prevalence of SARS-CoV-2 Infection at the University of Barcelona during the Third COVID-19 Pandemic Wave in Spain.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic started in December 2019 and still is a major global health challenge. Lockdown measures and social distancing sparked a global shift towards online learning, which deeply impacted universities' daily life, and the University of Barcelona (UB) was not an exception. Accordingly, we aimed to determine the impact of the SARS-CoV-2 pandemic at the UB. To that end, we performed a cross-sectional study on a sample of 2784 UB members (n = 52,529). Participants answered a brief, ad hoc, online epidemiological questionnaire and provided a nasal swab for reverse transcription polymerase chain reaction (RT-PCR) SARS-CoV-2 analysis and a venous blood sample for SARS-CoV-2 IgG antibody assay. Total prevalence of SARS-CoV-2 infection (positive RT-PCR or positive IgG) was 14.9% (95%CI 13.3 to 17.0%). Forty-four participants (1.6%, 95%CI: 1.2-2.1%) were positive for SARS-CoV-2 RT-PCR. IgG against SARS-CoV-2 was observed in 12.8% (95%CI: 11.6-14.1%) of participants. Overall, while waiting for population vaccination and/or increased herd immunity, we should concentrate on identifying and isolating new cases and their contacts.

Differential impact of mitigation policies and socioeconomic status on COVID-19 prevalence and social distancing in the United States.

BACKGROUND: The spread of COVID-19 has highlighted the long-standing health inequalities across the U.S. as neighborhoods with fewer resources were associated with higher rates of COVID-19 transmission. Although the stay-at-home order was one of the most effective methods to contain its spread, residents in lower-income neighborhoods faced barriers to practicing social distancing. We aimed to quantify the differential impact of stay-at-home policy on COVID-19 transmission and residents' mobility across neighborhoods of different levels of socioeconomic disadvantage. METHODS: This was a comparative interrupted time-series analysis at the county level. We included 2087 counties from 38 states which both implemented and lifted the state-wide stay-at-home order. Every county was assigned to one of four equally-sized groups based on its levels of disadvantage, represented by the Area Deprivation Index. Prevalence of COVID-19 was calculated by dividing the daily number of cumulative confirmed COVID-19 cases by the number of residents from the 2010 Census. We used the Social Distancing Index (SDI), derived from the COVID-19 Impact Analysis Platform, to measure the mobility. For the evaluation of implementation, the observation started from Mar 1st 2020 to 1 day before lifting; and, for lifting, it ranged from 1 day after implementation to Jul 5th 2020. We calculated a comparative change of daily trends in COVID-19 prevalence and Social Distancing Index between counties with three highest disadvantage levels and those with the least level before and after the implementation and lifting of the stay-at-home order, separately. RESULTS: On both stay-at-home implementation and lifting dates, COVID-19 prevalence was much higher among counties with the highest or lowest disadvantage level, while mobility decreased as the disadvantage level increased. Mobility of the most disadvantaged counties was least impacted by stay-at-home implementation and relaxation compared to counties with the most resources; however, disadvantaged counties experienced the largest relative increase in COVID-19 infection after both stay-at-home implementation and relaxation. CONCLUSIONS: Neighborhoods with varying levels of socioeconomic disadvantage reacted differently to the implementation and relaxation of COVID-19 mitigation policies. Policymakers should consider investing more resources in disadvantaged counties as the pandemic may not stop until most neighborhoods have it under control.

Prevalence of COVID-19 Infection in Asymptomatic Cancer Patients in a District With High Prevalence of SARS-CoV-2 in Italy.

Background Cancer patients are presumed a frail group at high risk to contract coronavirus disease (COVID-19). The aim of this study was to investigate the prevalence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection in asymptomatic cancer patients attending the outpatient clinic of a general hospital in a region with a high prevalence of SARS-CoV-2 infection (North Italy, first wave). Methods We retrospectively analyzed data of consecutive cancer patients attending the outpatient clinic of the oncology unit, General Hospital of Piacenza. All the patients having underlying cancer, without clinical suspicion of COVID-19, attending the outpatient clinic underwent nasopharyngeal swabs, from April 3, 2020 to June 3, 2020 and were included in this study. Results In a two-month period, 260 consecutive, asymptomatic (for COVID-19) cancer patients were tested for COVID-19. There were 160 women and 100 men; 218 patients were under active anticancer treatment, 32 in the diagnostic/staging phase waiting for treatment, and 10 treated with supportive care only. Ten of the 260 patients (3.85%) showed COVID-19 positivity. All but one (treated with hormone therapy) of the COVID-19 positive patients delayed anticancer treatment. The mean delay of anticancer treatment was 45.86±27.66 days (range 21-87 days), and the mean time for viral clearance was 25.7±22.68 days (range 7-79 days). All the 10 patients with COVID-19 and cancer overcame the infection, and treated patients could restart anticancer treatment. Conclusion Our data indicate a high prevalence of COVID-19 in cancer patients in an area with a high prevalence of SARS-CoV-2 infection. Routine COVID-19 testing of cancer patients when asymptomatic allowed an early detection, isolation, and treatment, avoiding viral spread among other frail patients and among medical/nurse staff.

Eliciting Beliefs about COVID-19 Prevalence and Mortality: Epidemiological Models Compared with The Street.

Subjective belief elicitation about uncertain events has a long lineage in the economics and statistics literatures. Recent developments in the experimental elicitation and statistical estimation of subjective belief distributions allow inferences about whether these beliefs are biased relative to expert opinion, and the confidence with which they are held. Beliefs about COVID-19 prevalence and mortality interact with risk management efforts, so it is important to understand relationships between these beliefs and publicly disseminated statistics, particularly those based on evolving epidemiological models. The pandemic provides a unique setting over which to bracket the range of possible COVID-19 prevalence and mortality outcomes given the proliferation of estimates from epidemiological models. We rely on the epidemiological model produced by the Institute for Health Metrics and Evaluation together with the set of epidemiological models summarised by FiveThirtyEight to bound prevalence and mortality outcomes for one-month, and December 1, 2020 time horizons. We develop a new method to partition these bounds into intervals, and ask subjects to place bets on these intervals, thereby revealing their beliefs. The intervals are constructed such that if beliefs are consistent with epidemiological models, subjects are best off betting the same amount on every interval. We use an incentivised experiment to elicit beliefs about COVID-19 prevalence and mortality from 598 students at Georgia State University, using six temporally-spaced waves between May and November 2020. We find that beliefs differ markedly from epidemiological models, which has implications for public health communication about the risks posed by the virus.

Prevalence of SARS-CoV-2 among community members presenting for testing in Peoria, Illinois from 21 April to 15 May 2020.

Expanding easily accessible community SARS-CoV-2 screening is essential in the response to the COVID-19 pandemic. In this report, we describe the findings from the initial 25 days of a SARS-CoV-2 drive-up and walk-up testing initiative was organized in Peoria, Illinois. Eighty-seven out of 4,073 individuals (2.1%) tested positive for SARS-CoV-2, and 46% of these were asymptomatic at the time of testing. There were ten frontline workers without symptoms consistent with COVID-19 who tested positive, including six that did not report any known exposure to SARS-CoV-2. These results stress the importance and effectiveness of widely available community SARS-CoV-2 testing and suggest a possible benefit to screening of asymptomatic individuals at higher risk for infection.

Early relaxation of community mitigation policies and risk of COVID-19 resurgence in the United States.

This study aimed to assess the impact of coronavirus disease (COVID-19) prevalence in the United States in the week leading to the relaxation of the stay-at-home orders (SAH) on future prevalence across states that implemented different SAH policies. We used data on the number of confirmed COVID-19 cases as of August 21, 2020 on county level. We classified states into four groups based on the 7-day change in prevalence and the state's approach to SAH policy. The groups included: (1) High Change (19 states; 7-day prevalence change ≥50th percentile), (2) Low Change (19 states; 7-day prevalence change <50th percentile), (3) No SAH (11 states: did not adopt SAH order), and (4) No SAH End (2 states: did not relax SAH order). We performed regression modeling assessing the association between change in prevalence at the time of SAH order relaxation and COVID-19 prevalence days after the relaxation of SAH order for four selected groups. After adjusting for other factors, compared to the High Change group, counties in the Low Change group had 33.8 (per 100,000 population) fewer cases (standard error (SE): 19.8, p < 0.001) 7 days after the relaxation of SAH order and the difference was larger by time passing. On August 21, 2020, the No SAH End group had 383.1 fewer cases (per 100,000 population) than the High Change group (SE: 143.6, p < 0.01). A measured, evidence-based approach is required to safely relax the community mitigation strategies and practice phased-reopening of the country.

SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases.

Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the N gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the S gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks.IMPORTANCE Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.

The relationship between trends in COVID-19 prevalence and traffic levels in South Korea.

OBJECTIVE: The World Health Organization (WHO) declared a COVID-19 pandemic on March 12, 2020. Several studies have indicated that densely populated urban environments and the heavy dependence on traffic could increase the potential spread of COVID-19. This study investigated the association between changes in traffic volume and the spread of COVID-19 in South Korea. METHODS: This study analyzed the daily national traffic and traffic trend for 3 months from January 1, 2020. Traffic data were measured using 6307 vehicle detection system (VDS). This study analyzed the difference in traffic levels between 2019 and 2020. Non-linear regression was performed to analyze the change in traffic trend in 2020. The relationship between traffic and confirmed COVID-19 cases was analyzed using single linear regression. RESULTS: The mean daily nationwide level of traffic for the first 3 months of 2020 was 143 655 563 vehicles, which was 9.7% lower than the same period in 2019 (159 044 566 vehicles). All regions showed a decreasing trend in traffic in February, which shifted to an increasing trend from March. In Incheon there was a positive, but insignificant, linear relationship between increasing numbers of newly confirmed cases and increasing traffic (ß = 43 146; p = 0.056). CONCLUSIONS: Numbers of newly confirmed COVID-19 patients have been decreasing since March, while the traffic has been increasing. The fact that traffic is increasing indicates greater contact between people, which in turn increases the risk of further COVID-19 spread. Therefore, the government will need to devise suitable policies, such as total social distancing.

Evaluating SARS-CoV-2 Seroconversion Following Relieve of Confinement Measures.

Seroprevalence studies are crucial both for estimating the prevalence of SARS-CoV-2 exposure and to provide a measure for the efficiency of the confinement measures. Portuguese universities were closed on March 16th 2020, when Portugal only registered 62 SARS-CoV-2 infection cases per million. We have validated a SARS-CoV-2 ELISA assay to a stabilized full-length spike protein using 216 pre-pandemic and 19 molecularly diagnosed SARS-CoV-2 positive individual's samples. At NOVA University of Lisbon, presential work was partially resumed on May 25th with staggered schedules. From June 15th to 30th, 3-4 weeks after the easing of confinement measures, we screened 1,636 collaborators of NOVA university of Lisbon for the presence of SARS-CoV-2 spike specific IgA and IgG antibodies. We found that spike-specific IgG in 50 of 1,636 participants (3.0%), none of which had anti-spike IgA antibodies. As participants self-reported as asymptomatic or paucisymptomatic, our study also provides a measurement of the prevalence of asymptomatic/paucisymptomatic SARS-CoV-2 infections. Our study suggests that essential workers have a 2-fold increase in viral exposure, when compared to non-essential workers that observed confinement. Additional serological surveys in different population subgroups will paint a broader picture of the effect of the confinement measures in the broader community.