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1.
Acs Es&T Water ; : 12, 2022.
Article in English | Web of Science | ID: covidwho-1927044

ABSTRACT

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater has been used to track community infections of coronavirus disease-2019 (COVID-19), providing critical information for public health interventions. Since levels in wastewater are dependent upon human inputs, we hypothesize that tracking infections can be improved by normalizing wastewater concentrations against indicators of human waste [Pepper Mild Mottle Virus (PMMoV), beta-2 Microglobulin (B2M), and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators of human waste in wastewater from two sewersheds of different scales: a University campus and a wastewater treatment plant. Wastewater data were combined with complementary COVID-19 case tracking to evaluate the efficiency of wastewater surveillance for forecasting new COVID-19 cases and, for the larger scale, hospitalizations. Results show that the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in improved correlations with COVID-19 cases for campus data using volcano second generation (V2G)-qPCR chemistry (r(s) = 0.69 without normalization, r(s) = 0.73 with normalization). Mixed results were obtained for normalization by PMMoV for samples collected at the community scale. Overall benefits from normalizing with measures of human waste depend upon qPCR chemistry and improves with smaller sewershed scale. We recommend further studies that evaluate the efficacy of additional normalization targets.

2.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-332635

ABSTRACT

Importance: Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples. Analysis of these samples can be employed for noninvasive surveillance of infectious diseases. Objective: To evaluate the efficacy of environmental surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for predicting COVID-19 cases in a college dormitory. Design: Using a prospective experimental design, air, surface swabs, and wastewater samples were collected from a college dormitory from March to May 2021. Students were randomly screened for COVID-19 during the study period. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 nd Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases. Setting: This study was conducted in a residential dormitory at the University of Miami, Coral Gables campus, FL, USA. The dormitory housed about 500 students. Participants: Students from the dormitory were randomly screened, for COVID-19 for 2-3 days / week while entering or exiting the dormitory. Main Outcome: Clinically diagnosed COVID-19 cases were of our main interest. We hypothesized that SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases in the dormitory, and SARS-CoV-2 can be detected in the environmental samples several days prior to the clinical diagnosis of COVID-19 cases. Results: SARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively. Conclusion: Proactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks. Key Points: Question: How effective is environmental surveillance of SARS-CoV-2 in public places for early detection of COVID-19 cases in a community?Findings: All clinically confirmed COVID-19 cases were predicted with the aid of 2 day lagged SARS-CoV-2 in environmental samples in a college dormitory. However, the prediction efficiency varied by sample type: best prediction by air samples, followed by wastewater and surface swab samples. SARS-CoV-2 was also detected in these samples even on days without any reported cases of COVID-19, suggesting underreporting of COVID-19 cases. Meaning: SARS-CoV-2 can be detected in environmental samples several days prior to clinical reporting of COVID-19 cases. Thus, proactive environmental surveillance of microbiome in public places can serve as a mean for early detection of location-time specific outbreaks of infectious diseases. It can also be used for underreporting of infectious diseases.

3.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-331037

ABSTRACT

IMPORTANCE: Genomic footprints of pathogens shed by infected individuals can be traced in environmental samples, which can serve as a noninvasive method for infectious disease surveillance. OBJECTIVE: To determine the efficacy of predicting COVID-19 cases using the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) found in air, surface swabs and wastewater samples. DESIGN: A prospective experimental design utilizing randomized surveillance of air, surface, and wastewater samples was performed from March to May 2021. SARS-CoV-2 in environmental samples was concentrated with electronegative filtration and quantified using Volcano 2 (nd) Generation-qPCR. Descriptive analyses were conducted to examine the associations between time-lagged SARS-CoV-2 in environmental samples and clinically diagnosed COVID-19 cases. SETTING: This study was conducted in a residential dormitory at the University of Miami, Coral Gables campus. PARTICIPANTS: Random air and surface swab samples were collected in high-traffic areas of a college dormitory, housing roughly 500 students, with the number of individuals contributing at any point in time. Wastewater was collected from the dormitory where individuals from the resident population as well as any visitors of the building contributed to the sewer system. Students from the dormitory were randomly screened for COVID-19 for 2-3 days / week. MAIN OUTCOME: SARS-CoV-2 detection in environmental samples was an indicator of the presence of local COVID-19 cases and a 2-day lead indicator for a potential outbreak at the dormitory building scale. The hypothesis being tested was formulated prior to the data collection. RESULTS: A total of 445 air, surface swab and wastewater samples were collected, and these data were aggregated by day. SARS-CoV-2 genomic footprints were detected in air, surface swab and wastewater samples on 52 (63.4%), 40 (50.0%) and 57 (68.6%) days, respectively, during the study period. On 19 (24%) of 78 days SARS-CoV-2 was detected in all three sample types. Clinically diagnosed COVID-19 cases were reported on 11 days during the study period and SARS-CoV-2 was also detected two days before the case diagnosis on all 11 (100%), 9 (81.8%) and 8 (72.7%) days in air, surface swab and wastewater samples, respectively. CONCLUSION: Proactive environmental surveillance of SARS-CoV-2 or other pathogens in a community/public setting has potential to guide targeted measures to contain and/or mitigate infectious disease outbreaks. KEY POINTS: Question: Could environmental surveillance provide a means of early detection for SARS-CoV-2 in high population communities, such as college campuses, or even cities?Findings: In this surveillance study, SARS-CoV-2 was detected from air, surface swab, and wastewater samples of a college dormitory in 165 (30%) of 445 total samples collected. When assessed alone, each sample type offered a means for predicting COVID-19 clinical cases (∼90%), however when aggregated, provided a prediction rate of roughly 100% for detecting SARS-CoV-2 within the community.Meaning: The findings suggest that the early detection of SARS-CoV-2 from environmental sampling including active air, surface swab, and wastewater surveillance provide an accurate and early means of detecting COVID-19 infection within high population communities.

4.
Topics in Antiviral Medicine ; 29(1):88, 2021.
Article in English | EMBASE | ID: covidwho-1250567

ABSTRACT

Background: Immune dysfunction characterized by lower antibody (Ab) response to infection or vaccination has been well described among People Living with HIV (PLWH), but due to the novelty of the SARS-CoV-2 virus has not been evaluated among PLWH coinfected with SARS-CoV-2. This study compared the magnitude and longevity of Ab response to SARS-CoV-2 in a group of HIV+ and HIV-individuals infected with SARS-CoV-2 Methods: 17 HIV+COVID+ and 19 HIV-COVID+ participants were recruited from the community as part of the ACTION study and followed longitudinally at day 14, 1 month and 3 months. HIV+ were on effective ART (plasma viral load <500 copies/ml). SARS-CoV-2 infection was confirmed by SARS-COV2 DNA PCR and rapid antibody test. All participants had mild/moderate COVID-19 without hospitalization. Antibody responses (IgG and IgM) were measured using an indirect in house developed ELISA using spike RBD antigen (courtesy, Scott Boyd, Stanford University) and the data are expressed as relative Ab units based on the positive control standard. Results: The median age of HIV+ participants was 55 (26-63) with 23.5% (4/17) females. The median age for HIV-was 38 (27-78) with 57.8% (11/19) females. Time from COVID-19 diagnosis was 26 days for HIV+ and 21 for HIV-. Mean CD4 count for the HIV+ participants was 859.5 ± 287.2 cells/μl. Longitudinal analysis did not show a significant reduction in Ab response at 3 months in either HIV+ or HIV-groups. Levels of SARS-CoV-2 RBD specific IgM and IgG responses did not differ significantly between HIV+ and HIV-at any timepoint although there was a trend of lower IgM and IgG responses at 3 months in both groups compared to entry levels. Age was correlated with IgG response at day 14 (r =0.6, p = 0.02), 1 month (r =0.6, p = 0.014) and 3 month(r =0.87, p = 0.0008) in HIV+ and weakly correlated at day 14 (r =0.46, p = 0.04) in HIV-. Absolute CD4 count was not correlated with IgM and IgG responses in HIV+. Conclusion: The magnitude and persistence of Ab response to SARS-CoV-2 infection in the 3-4 months post-infection does not differ by HIV status. Although extended longitudinal follow-ups are required to gain insights about the longevity of Ab responses in HIV+ individuals, results suggest that immune protection and vaccine responses may not differ by HIV status.

5.
Diagnostics ; 11(4):09, 2021.
Article in English | MEDLINE | ID: covidwho-1209859

ABSTRACT

Accurate phenotyping of patients with pulmonary hypertension (PH) is an integral part of informing disease classification, treatment, and prognosis. The impact of lung disease on PH outcomes and response to treatment remains a challenging area with limited progress. Imaging with computed tomography (CT) plays an important role in patients with suspected PH when assessing for parenchymal lung disease, however, current assessments are limited by their semi-qualitative nature. Quantitative chest-CT (QCT) allows numerical quantification of lung parenchymal disease beyond subjective visual assessment. This has facilitated advances in radiological assessment and clinical correlation of a range of lung diseases including emphysema, interstitial lung disease, and coronavirus disease 2019 (COVID-19). Artificial Intelligence approaches have the potential to facilitate rapid quantitative assessments. Benefits of cross-sectional imaging include ease and speed of scan acquisition, repeatability and the potential for novel insights beyond visual assessment alone. Potential clinical benefits include improved phenotyping and prediction of treatment response and survival. Artificial intelligence approaches also have the potential to aid more focused study of pulmonary arterial hypertension (PAH) therapies by identifying more homogeneous subgroups of patients with lung disease. This state-of-the-art review summarizes recent QCT developments and potential applications in patients with PH with a focus on lung disease.

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