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Huang AA, Huang SY. Diabetes is associated with increased risk of death in COVID-19 hospitalizations in Mexico 2020: A retrospective cohort study. Health Sci Rep 2023; 6:e1416. [PMID: 37415678 PMCID: PMC10320697 DOI: 10.1002/hsr2.1416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 06/14/2023] [Accepted: 06/27/2023] [Indexed: 07/08/2023] Open
Abstract
Background and Aim The COVID-19 disease course can be thought of as a function of prior risk factors consisting of comorbidities and outcomes. Survival analysis data for diabetic patients with COVID-19 from an up to date and representative sample can increase efficiency in resource allocation. The study aimed to quantify mortality in Mexico for individuals with diabetes in the setting of COVID-19 hospitalization. Methods This retrospective cohort study utilized publicly available data from the Mexican Federal Government, covering the period from April 14, 2020, to December 20, 2020 (last accessed). Survival analysis techniques were applied, including Kaplan-Meier curves to estimate survival probabilities, log-rank tests to compare survival between groups, Cox proportional hazard models to assess the association between diabetes and mortality risk, and restricted mean survival time (RMST) analyses to measure the average survival time. Results A total of 402,388 adults age greater than 18 with COVID-19 were used in the analysis. Mean age = 16.16 (SD = 15.55), 214,161 males (53%). Twenty-day Kaplan-Meier estimates of mortality were 32% for COVID-19 patients with diabetes and 10.2% for those without diabetes with log-rank p < 0.01. Univariable analysis showed increased mortality in diabetic patients (hazard ratio [HR]: 3.61, 95% confidence interval [CI]: 3.54-3.67, p < 0.01) showing a 254% increase in death. After controlling for confounding variables, multivariate analysis continued to show increased mortality in diabetics (HR: 1.37, 95% CI: 1.29-1.44, p < 0.01) indicating a 37% increase in death. Multivariable RMST at Day 20 showed in Mexico, hospitalized COVID-19 patients were associated with less mean survival time by 2.01 days (p < 0.01) and a 10% increased mortality (p < 0.01). Conclusions In the present analysis, COVID-19 patients with diabetes in Mexico had shorter survival times. Further interventions aimed at improving comorbidities in the population, particularly in individuals with diabetes, may contribute to better outcomes in COVID-19 patients.
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Affiliation(s)
- Alexander A. Huang
- Department of MD EducationNorthwestern University Feinberg School of MedicineChicagoIllinoisUSA
| | - Samuel Y. Huang
- Department of Internal MedicineVirginia Commonwealth University School of MedicineRichmondVirginiaUSA
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Xie Y, Challis JK, Oloye FF, Asadi M, Cantin J, Brinkmann M, McPhedran KN, Hogan N, Sadowski M, Jones PD, Landgraff C, Mangat C, Servos MR, Giesy JP. RNA in Municipal Wastewater Reveals Magnitudes of COVID-19 Outbreaks across Four Waves Driven by SARS-CoV-2 Variants of Concern. ACS ES&T WATER 2022; 2:1852-1862. [PMID: 37552734 PMCID: PMC8887651 DOI: 10.1021/acsestwater.1c00349] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 02/10/2022] [Accepted: 02/11/2022] [Indexed: 05/07/2023]
Abstract
There are no standardized protocols for quantifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in wastewater to date, especially for population normalization. Here, a pipeline was developed, applied, and assessed to quantify SARS-CoV-2 and key variants of concern (VOCs) RNA in wastewater at Saskatoon, Canada. Normalization approaches using recovery ratio and extraction efficiency, wastewater parameters, or population indicators were assessed by comparing to daily numbers of new cases. Viral load was positively correlated with daily new cases reported in the sewershed. Wastewater surveillance (WS) had a lead time of approximately 7 days, which indicated surges in the number of new cases. WS revealed the variant α and δ driving the third and fourth wave, respectively. The adjustment with the recovery ratio and extraction efficiency improved the correlation between viral load and daily new cases. Normalization of viral concentration to concentrations of the artificial sweetener acesulfame K improved the trend of viral load during the Christmas and New Year holidays when populations were dynamic and variable. Acesulfame K performed better than pepper mild mottle virus, creatinine, and ammonia for population normalization. Hence, quality controls to characterize recovery ratios and extraction efficiencies and population normalization with acesulfame are promising for precise WS programs supporting decision-making in public health.
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Affiliation(s)
- Yuwei Xie
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Jonathan K. Challis
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Femi F. Oloye
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Mohsen Asadi
- Department of Civil, Geological and Environmental
Engineering, College of Engineering, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5A9,
Canada
| | - Jenna Cantin
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Markus Brinkmann
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- School of Environment and Sustainability,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- Global Institute for Water Security,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 3H5,
Canada
| | - Kerry N. McPhedran
- Department of Civil, Geological and Environmental
Engineering, College of Engineering, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5A9,
Canada
- Global Institute for Water Security,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 3H5,
Canada
| | - Natacha Hogan
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- College of Agriculture and Bioresources, Department of
Animal and Poultry Sciences, University of Saskatchewan,
Saskatoon, Saskatchewan S7N 5A8, Canada
| | - Mike Sadowski
- Wastewater Treatment Plant, Saskatoon Water Department,
City of Saskatoon, Saskatoon, Saskatchewan S7M 1X5,
Canada
| | - Paul D. Jones
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- School of Environment and Sustainability,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
| | - Chrystal Landgraff
- Division of Enteric Diseases, National Microbiology
Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba
R3E 3R2, Canada
- Food Science Department, University of
Guelph, Guelph, Ontario N1G 2W1, Canada
| | - Chand Mangat
- Antimicrobial Resistance and Nosocomial Infections,
National Microbiology Laboratory, Public Health Agency of
Canada, Winnipeg, Manitoba R3E 3R2, Canada
| | - Mark R. Servos
- Department of Biology, University of
Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - John P. Giesy
- Toxicology Centre, University of
Saskatchewan, Saskatoon, Saskatchewan S7N 5B3,
Canada
- Department of Veterinary Biomedical Sciences,
University of Saskatchewan, Saskatoon, Saskatchewan S7N 5B4,
Canada
- Department of Environmental Sciences,
Baylor University, Waco, Texas 76706, United
States
- Department of Zoology and Center for Integrative
Toxicology, Michigan State University, East Lansing, Michigan
48824, United States
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3
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Oloye FF, Xie Y, Asadi M, Cantin J, Challis JK, Brinkmann M, McPhedran KN, Kristian K, Keller M, Sadowski M, Jones PD, Landgraff C, Mangat C, Fuzzen M, Servos MR, Giesy JP. Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 841:156741. [PMID: 35716745 PMCID: PMC9212401 DOI: 10.1016/j.scitotenv.2022.156741] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 05/21/2023]
Abstract
Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.
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Affiliation(s)
- Femi F Oloye
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada.
| | - Yuwei Xie
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada.
| | - Mohsen Asadi
- Department of Civil, Geological and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jenna Cantin
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jonathan K Challis
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada
| | - Markus Brinkmann
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada; Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Kerry N McPhedran
- Department of Civil, Geological and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - Kevin Kristian
- Wastewater Treatment Plant, Public Work Department, City of Prince Albert, Prince Albert, SK, Canada
| | - Mark Keller
- Wastewater Treatment Plant, City Operations, City of North Battleford, North Battleford, SK, Canada
| | - Mike Sadowski
- Wastewater Treatment Plant, Saskatoon Water Department, City of Saskatoon, Saskatoon, SK, Canada
| | - Paul D Jones
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada
| | - Chrystal Landgraff
- Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Chand Mangat
- Wastewater Surveillance Unit, National Microbiology Laboratory Winnipeg, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - John P Giesy
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; Department of Veterinary Biomedical Sciences, University of Saskatchewan, Saskatoon, SK, Canada; Department of Environmental Sciences, Baylor University, Waco, TX, USA; Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA.
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4
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Oloye FF, Xie Y, Asadi M, Cantin J, Challis JK, Brinkmann M, McPhedran KN, Kristian K, Keller M, Sadowski M, Jones PD, Landgraff C, Mangat C, Fuzzen M, Servos MR, Giesy JP. Rapid transition between SARS-CoV-2 variants of concern Delta and Omicron detected by monitoring municipal wastewater from three Canadian cities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022. [PMID: 35716745 PMCID: PMC8887651 DOI: 10.1021/acsestwater.1c00349&ref=pdf] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities.
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Affiliation(s)
- Femi F Oloye
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada.
| | - Yuwei Xie
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada.
| | - Mohsen Asadi
- Department of Civil, Geological and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jenna Cantin
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada
| | - Jonathan K Challis
- Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada
| | - Markus Brinkmann
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; School of Environment and Sustainability, University of Saskatchewan, Saskatoon, SK, Canada; Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada
| | - Kerry N McPhedran
- Department of Civil, Geological and Environmental Engineering, College of Engineering, University of Saskatchewan, Saskatoon, SK, Canada
| | - Kevin Kristian
- Wastewater Treatment Plant, Public Work Department, City of Prince Albert, Prince Albert, SK, Canada
| | - Mark Keller
- Wastewater Treatment Plant, City Operations, City of North Battleford, North Battleford, SK, Canada
| | - Mike Sadowski
- Wastewater Treatment Plant, Saskatoon Water Department, City of Saskatoon, Saskatoon, SK, Canada
| | - Paul D Jones
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada
| | - Chrystal Landgraff
- Division of Enteric Diseases, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Chand Mangat
- Wastewater Surveillance Unit, National Microbiology Laboratory Winnipeg, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Meghan Fuzzen
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Mark R Servos
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - John P Giesy
- Toxicology Centre, University of Saskatchewan, Saskatoon, SK, Canada; Department of Veterinary Biomedical Sciences, University of Saskatchewan, Saskatoon, SK, Canada; Department of Environmental Sciences, Baylor University, Waco, TX, USA; Department of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, MI, USA.
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