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1.
Preprint | EuropePMC | ID: ppcovidwho-296998

ABSTRACT

Study objective: To garner a framework for combining community wastewater surveillance with state clinical surveillance that influence confirmation of SARS-CoV-2 variants within the community, and recommend how the flow of such research evidence could be expanded and employed for public health response. Design, setting, and participants: This work involved analyzing wastewater samples collected weekly from 17 geographically resolved locations in Louisville/Jefferson County, Kentucky from February 10 to November 29, 2021. Genomic surveillance and RT-qPCR platforms were used as screening to identify SARS-CoV-2 in wastewater, and state clinical surveillance was used for confirmation. Main results: The results demonstrate increased epidemiological value of combining community wastewater genomic surveillance and RT-qPCR with conventional case auditing methods. The spatial scale and temporal frequency of wastewater sampling provides promising sensitivity and specificity to be useful to gain public health screening insights about community emergence, seeding, and spread. Conclusions: Better national surveillance systems are needed for future pathogens and variants, and wastewater-based genomic surveillance represents opportune coupling. This paper presents current evidence that complementary wastewater and clinical testing is enhanced cost-effectively when linked;making a strong case for a joint public health framework. The findings suggest significant potential for rapid progress to be made in extending this work to consider pathogens of interest as a whole within wastewater, which could be examined in either a targeted fashion as we currently do with SARS-CoV-2 or in terms of a global monitoring of all pathogens found, and developing evidence based public health practice to best support community health.

2.
Water Res ; 205: 117710, 2021 Oct 15.
Article in English | MEDLINE | ID: covidwho-1450241

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) likely emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 548 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the novel SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.


Subject(s)
COVID-19 , SARS-CoV-2 , High-Throughput Nucleotide Sequencing , Humans , Pandemics , Waste Water
3.
Pathogens ; 10(10)2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1444290

ABSTRACT

Throughout the course of the ongoing SARS-CoV-2 pandemic there has been a need for approaches that enable rapid monitoring of public health using an unbiased and minimally invasive means. A major way this has been accomplished is through the regular assessment of wastewater samples by qRT-PCR to detect the prevalence of viral nucleic acid with respect to time and location. Further expansion of SARS-CoV-2 wastewater monitoring efforts to include the detection of variants of interest/concern through next-generation sequencing has enhanced the understanding of the SARS-CoV-2 outbreak. In this report, we detail the results of a collaborative effort between public health and metropolitan wastewater management authorities and the University of Louisville to monitor the SARS-CoV-2 pandemic through the monitoring of aggregate wastewater samples over a period of 28 weeks. Through the use of next-generation sequencing approaches the polymorphism signatures of Variants of Concern/Interest were evaluated to determine the likelihood of their prevalence within the community on the basis of their relative dominance within sequence datasets. Our data indicate that wastewater monitoring of water quality treatment centers and smaller neighborhood-scale catchment areas is a viable means by which the prevalence and genetic variation of SARS-CoV-2 within a metropolitan community of approximately one million individuals may be monitored, as our efforts detected the introduction and emergence of variants of concern in the city of Louisville. Importantly, these efforts confirm that regional emergence and spread of variants of interest/concern may be detected as readily in aggregate wastewater samples as compared to the individual wastewater sheds. Furthermore, the information gained from these efforts enabled targeted public health efforts including increased outreach to at-risk communities and the deployment of mobile or community-focused vaccination campaigns.

4.
Sci Rep ; 11(1): 18285, 2021 09 14.
Article in English | MEDLINE | ID: covidwho-1410888

ABSTRACT

Serological assays intended for diagnosis, sero-epidemiologic assessment, and measurement of protective antibody titers upon infection or vaccination are essential for managing the SARS-CoV-2 pandemic. Serological assays measuring the antibody responses against SARS-CoV-2 antigens are readily available. However, some lack appropriate characteristics to accurately measure SARS-CoV-2 antibodies titers and neutralization. We developed an Enzyme-linked Immunosorbent Assay (ELISA) methods for measuring IgG, IgA, and IgM responses to SARS-CoV-2, Spike (S), receptor binding domain (RBD), and nucleocapsid (N) proteins. Performance characteristics of sensitivity and specificity have been defined. ELISA results show positive correlation with microneutralization and Plaque Reduction Neutralization assays with infectious SARS-CoV-2. Our ELISA was used to screen healthcare workers in Louisville, KY during the first wave of the local pandemic in the months of May and July 2020. We found a seropositive rate of approximately 1.4% and 2.3%, respectively. Our analyses demonstrate a broad immune response among individuals and suggest some non-RBD specific S IgG and IgA antibodies neutralize SARS-CoV-2.


Subject(s)
Antibodies, Viral/blood , COVID-19/epidemiology , SARS-CoV-2/immunology , Area Under Curve , COVID-19/blood , COVID-19/virology , Coronavirus Nucleocapsid Proteins/immunology , Enzyme-Linked Immunosorbent Assay , Humans , Immunoglobulin A/blood , Immunoglobulin G/blood , Immunoglobulin M/blood , Kentucky/epidemiology , Pandemics , Phosphoproteins/immunology , ROC Curve , SARS-CoV-2/isolation & purification , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/immunology
5.
PLoS One ; 16(2): e0246167, 2021.
Article in English | MEDLINE | ID: covidwho-1088752

ABSTRACT

IMPORTANCE: Intensity and duration of the COVID-19 pandemic, and planning required to balance concerns of saving lives and avoiding economic collapse, could depend significantly on whether SARS-CoV-2 transmission is sensitive to seasonal changes. OBJECTIVE: Hypothesis is that increasing temperature results in reduced SARS CoV-2 transmission and may help slow the increase of cases over time. SETTING: Fifty representative Northern Hemisphere countries meeting specific criteria had sufficient COVID-19 case and meteorological data for analysis. METHODS: Regression was used to find the relationship between the log of number of COVID-19 cases and temperature over time in 50 representative countries. To summarize the day-day variability, and reduce dimensionality, we selected a robust measure, Coefficient of Time (CT), for each location. The resulting regression coefficients were then used in a multivariable regression against meteorological, country-level and demographic covariates. RESULTS: Median minimum daily temperature showed the strongest correlation with the reciprocal of CT (which can be considered as a rate associated with doubling time) for confirmed cases (adjusted R2 = 0.610, p = 1.45E-06). A similar correlation was found using median daily dewpoint, which was highly colinear with temperature, and therefore was not used in the analysis. The correlation between minimum median temperature and the rate of increase of the log of confirmed cases was 47% and 45% greater than for cases of death and recovered cases of COVID-19, respectively. This suggests the primary influence of temperature is on SARS-CoV-2 transmission more than COVID-19 morbidity. Based on the correlation between temperature and the rate of increase in COVID-19, it can be estimated that, between the range of 30 to 100 degrees Fahrenheit, a one degree increase is associated with a 1% decrease-and a one degree decrease could be associated with a 3.7% increase-in the rate of increase of the log of daily confirmed cases. This model of the effect of decreasing temperatures can only be verified over time as the pandemic proceeds through colder months. CONCLUSIONS: The results suggest that boreal summer months are associated with slower rates of COVID-19 transmission, consistent with the behavior of a seasonal respiratory virus. Knowledge of COVID-19 seasonality could prove useful in local planning for phased reductions social interventions and help to prepare for the timing of possible pandemic resurgence during cooler months.


Subject(s)
COVID-19/transmission , SARS-CoV-2/physiology , COVID-19/metabolism , Hot Temperature , Humans , Meteorological Concepts , Pandemics , SARS-CoV-2/isolation & purification , Seasons , Weather
6.
BMC Med Res Methodol ; 20(1): 220, 2020 08 31.
Article in English | MEDLINE | ID: covidwho-736373

ABSTRACT

BACKGROUND: Because of unknown features of the COVID-19 and the complexity of the population affected, standard clinical trial designs on treatments may not be optimal in such patients. We propose two independent clinical trials designs based on careful grouping of patient and outcome measures. METHODS: Using the World Health Organization ordinal scale on patient status, we classify treatable patients (Stages 3-7) into two risk groups. Patients in Stages 3, 4 and 5 are categorized as the intermediate-risk group, while patients in Stages 6 and 7 are categorized as the high-risk group. To ensure that an intervention, if deemed efficacious, is promptly made available to vulnerable patients, we propose a group sequential design incorporating four factors stratification, two interim analyses, and a toxicity monitoring rule for the intermediate-risk group. The primary response variable (binary variable) is based on the proportion of patients discharged from hospital by the 15th day. The goal is to detect a significant improvement in this response rate. For the high-risk group, we propose a group sequential design incorporating three factors stratification, and two interim analyses, with no toxicity monitoring. The primary response variable for this design is 30 day mortality, with the goal of detecting a meaningful reduction in mortality rate. RESULTS: Required sample size and toxicity boundaries are calculated for each scenario. Sample size requirements for designs with interim analyses are marginally greater than ones without. In addition, for both the intermediate-risk group and the high-risk group, the required sample size with two interim analyses is almost identical to analyses with just one interim analysis. CONCLUSIONS: We recommend using a binary outcome with composite endpoints for patients in Stage 3, 4 or 5 with a power of 90% to detect an improvement of 20% in the response rate, and a 30 day mortality rate outcome for those in Stage 6 or 7 with a power of 90% to detect 15% (effect size) reduction in mortality rate. For the intermediate-risk group, two interim analyses for efficacy evaluation along with toxicity monitoring are encouraged. For the high-risk group, two interim analyses without toxicity monitoring is advised.


Subject(s)
Betacoronavirus , Coronavirus Infections/therapy , Data Interpretation, Statistical , Pneumonia, Viral/therapy , Research Design , COVID-19 , Clinical Trials, Phase II as Topic , Clinical Trials, Phase III as Topic , Humans , Outcome Assessment, Health Care , Pandemics , SARS-CoV-2
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