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      Show us the data: global COVID-19 wastewater monitoring efforts, equity, and gaps

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          Abstract

          A year since the declaration of the global coronavirus disease 2019 (COVID-19) pandemic, there were over 110 million cases and 2.5 million deaths. Learning from methods to track community spread of other viruses such as poliovirus, environmental virologists and those in the wastewater-based epidemiology (WBE) field quickly adapted their existing methods to detect SARS-CoV-2 RNA in wastewater. Unlike COVID-19 case and mortality data, there was not a global dashboard to track wastewater monitoring of SARS-CoV-2 RNA worldwide. This study provides a 1-year review of the “COVIDPoops19” global dashboard of universities, sites, and countries monitoring SARS-CoV-2 RNA in wastewater. Methods to assemble the dashboard combined standard literature review, Google Form submissions, and daily, social media keyword searches. Over 200 universities, 1400 sites, and 55 countries with 59 dashboards monitored wastewater for SARS-CoV-2 RNA. However, monitoring was primarily in high-income countries (65%) with less access to this valuable tool in low- and middle-income countries (35%). Data were not widely shared publicly or accessible to researchers to further inform public health actions, perform meta-analysis, better coordinate, and determine equitable distribution of monitoring sites. For WBE to be used to its full potential during COVID-19 and beyond, show us the data.

          Abstract

          Analysis of a global dashboard of COVID-19 wastewater monitoring indicates that most monitoring is in High Income Countries and there is a need for great equity and open data sharing.

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            WHO Declares COVID-19 a Pandemic

            The World Health Organization (WHO) on March 11, 2020, has declared the novel coronavirus (COVID-19) outbreak a global pandemic (1). At a news briefing, WHO Director-General, Dr. Tedros Adhanom Ghebreyesus, noted that over the past 2 weeks, the number of cases outside China increased 13-fold and the number of countries with cases increased threefold. Further increases are expected. He said that the WHO is “deeply concerned both by the alarming levels of spread and severity and by the alarming levels of inaction,” and he called on countries to take action now to contain the virus. “We should double down,” he said. “We should be more aggressive.” Among the WHO’s current recommendations, people with mild respiratory symptoms should be encouraged to isolate themselves, and social distancing is emphasized and these recommendations apply even to countries with no reported cases (2). Separately, in JAMA, researchers report that SARS-CoV-2, the virus that causes COVID-19, was most often detected in respiratory samples from patients in China. However, live virus was also found in feces. They conclude: “Transmission of the virus by respiratory and extrarespiratory routes may help explain the rapid spread of disease.”(3). COVID-19 is a novel disease with an incompletely described clinical course, especially for children. In a recente report W. Liu et al described that the virus causing Covid-19 was detected early in the epidemic in 6 (1.6%) out of 366 children (≤16 years of age) hospitalized because of respiratory infections at Tongji Hospital, around Wuhan. All these six children had previously been completely healthy and their clinical characteristics at admission included high fever (>39°C) cough and vomiting (only in four). Four of the six patients had pneumonia, and only one required intensive care. All patients were treated with antiviral agents, antibiotic agents, and supportive therapies, and recovered after a median 7.5 days of hospitalization. (4). Risk factors for severe illness remain uncertain (although older age and comorbidity have emerged as likely important factors), the safety of supportive care strategies such as oxygen by high-flow nasal cannula and noninvasive ventilation are unclear, and the risk of mortality, even among critically ill patients, is uncertain. There are no proven effective specific treatment strategies, and the risk-benefit ratio for commonly used treatments such as corticosteroids is unclear (3,5). Septic shock and specific organ dysfunction such as acute kidney injury appear to occur in a significant proportion of patients with COVID-19–related critical illness and are associated with increasing mortality, with management recommendations following available evidence-based guidelines (3). Novel COVID-19 “can often present as a common cold-like illness,” wrote Roman Wöelfel et al. (6). They report data from a study concerning nine young- to middle-aged adults in Germany who developed COVID-19 after close contact with a known case. All had generally mild clinical courses; seven had upper respiratory tract disease, and two had limited involvement of the lower respiratory tract. Pharyngeal virus shedding was high during the first week of symptoms, peaking on day 4. Additionally, sputum viral shedding persisted after symptom resolution. The German researchers say the current case definition for COVID-19, which emphasizes lower respiratory tract disease, may need to be adjusted(6). But they considered only young and “normal” subjecta whereas the story is different in frail comorbid older patients, in whom COVID 19 may precipitate an insterstitial pneumonia, with severe respiratory failure and death (3). High level of attention should be paid to comorbidities in the treatment of COVID-19. In the literature, COVID-19 is characterised by the symptoms of viral pneumonia such as fever, fatigue, dry cough, and lymphopenia. Many of the older patients who become severely ill have evidence of underlying illness such as cardiovascular disease, liver disease, kidney disease, or malignant tumours. These patients often die of their original comorbidities. They die “with COVID”, but were extremely frail and we therefore need to accurately evaluate all original comorbidities. In addition to the risk of group transmission of an infectious disease, we should pay full attention to the treatment of the original comorbidities of the individual while treating pneumonia, especially in older patients with serious comorbid conditions and polipharmacy. Not only capable of causing pneumonia, COVID-19 may also cause damage to other organs such as the heart, the liver, and the kidneys, as well as to organ systems such as the blood and the immune system. Patients die of multiple organ failure, shock, acute respiratory distress syndrome, heart failure, arrhythmias, and renal failure (5,6). What we know about COVID 19? In December 2019, a cluster of severe pneumonia cases of unknown cause was reported in Wuhan, Hubei province, China. The initial cluster was epidemiologically linked to a seafood wholesale market in Wuhan, although many of the initial 41 cases were later reported to have no known exposure to the market (7). A novel strain of coronavirus belonging to the same family of viruses that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), as well as the 4 human coronaviruses associated with the common cold, was subsequently isolated from lower respiratory tract samples of 4 cases on 7 January 2020. On 30 January 2020, the WHO declared that the SARS-CoV-2 outbreak constituted a Public Health Emergency of International Concern, and more than 80, 000 confirmed cases had been reported worldwide as of 28 February 2020 (8). On 31 January 2020, the U.S. Centers for Disease Control and Prevention announced that all citizens returning from Hubei province, China, would be subject to mandatory quarantine for up to 14 days. But from China COVID 19 arrived to many other countries. Rothe C et al reported a case of a 33-year-old otherwise healthy German businessman :she became ill with a sore throat, chills, and myalgias on January 24, 2020 (9). The following day, a fever of 39.1°C developed, along with a productive cough. By the evening of the next day, he started feeling better and went back to work on January 27. Before the onset of symptoms, he had attended meetings with a Chinese business partner at his company near Munich on January 20 and 21. The business partner, a Shanghai resident, had visited Germany between January 19 and 22. During her stay, she had been well with no signs or symptoms of infection but had become ill on her flight back to China, where she tested positive for 2019-nCoV on January 26. This case of 2019-nCoV infection was diagnosed in Germany and transmitted outside Asia. However, it is notable that the infection appears to have been transmitted during the incubation period of the index patient, in whom the illness was brief and nonspecific. The fact that asymptomatic persons are potential sources of 2019-nCoV infection may warrant a reassessment of transmission dynamics of the current outbreak (9). Our current understanding of the incubation period for COVID-19 is limited. An early analysis based on 88 confirmed cases in Chinese provinces outside Wuhan, using data on known travel to and from Wuhan to estimate the exposure interval, indicated a mean incubation period of 6.4 days (95% CI, 5.6 to 7.7 days), with a range of 2.1 to 11.1 days. Another analysis based on 158 confirmed cases outside Wuhan estimated a median incubation period of 5.0 days (CI, 4.4 to 5.6 days), with a range of 2 to 14 days. These estimates are generally consistent with estimates from 10 confirmed cases in China (mean incubation period, 5.2 days [CI, 4.1 to 7.0 days] and from clinical reports of a familial cluster of COVID-19 in which symptom onset occurred 3 to 6 days after assumed exposure in Wuhan (10-12). The incubation period can inform several important public health activities for infectious diseases, including active monitoring, surveillance, control, and modeling. Active monitoring requires potentially exposed persons to contact local health authorities to report their health status every day. Understanding the length of active monitoring needed to limit the risk for missing infections is necessary for health departments to effectively use resources. A recent paper provides additional evidence for a median incubation period for COVID-19 of approximately 5 days (13). Lauer et al suggest that 101 out of every 10 000 cases will develop symptoms after 14 days of active monitoring or quarantinen (13). Whether this rate is acceptable depends on the expected risk for infection in the population being monitored and considered judgment about the cost of missing cases. Combining these judgments with the estimates presented here can help public health officials to set rational and evidence-based COVID-19 control policies. Note that the proportion of mild cases detected has increased as surveillance and monitoring systems have been strengthened. The incubation period for these severe cases may differ from that of less severe or subclinical infections and is not typically an applicable measure for those with asymptomatic infections In conclusion, in a very short period health care systems and society have been severely challenged by yet another emerging virus. Preventing transmission and slowing the rate of new infections are the primary goals; however, the concern of COVID-19 causing critical illness and death is at the core of public anxiety. The critical care community has enormous experience in treating severe acute respiratory infections every year, often from uncertain causes. The care of severely ill patients, in particular older persons with COVID-19 must be grounded in this evidence base and, in parallel, ensure that learning from each patient could be of great importance to care all population,
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              COVID-19 and Racial/Ethnic Disparities

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                Author and article information

                Contributors
                Journal
                FEMS Microbes
                FEMS Microbes
                femsmicrobes
                FEMS Microbes
                Oxford University Press
                2633-6685
                2023
                12 January 2023
                12 January 2023
                : 4
                : xtad003
                Affiliations
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering, University of California, Merced , Merced, CA 95343, United States
                Department of Civil and Environmental Engineering and Earth Science, University of Notre Dame , 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
                Department of Civil and Environmental Engineering and Earth Science, University of Notre Dame , 156 Fitzpatrick Hall, Notre Dame, IN 46556, United States
                KWR Water Research Institute , Groningenhaven 7, 3433 PE Nieuwegein, The Netherlands
                Civil Engineering and Geosciences, Delft University of Technology , Stevinweg 1, 2628 CN Delft, The Netherlands
                Michigan State University , 1405 S Harrison Rd, East-Lansing, MI 48823, United States
                CSIRO Land and Water, Ecosciences Precinct , 41 Boggo Road, QLD 4102, Australia
                Venthic Technologies , Kipoupoleos 129, Peristeri, Athens 12137, Greece
                PATH 2201 Westlake Avenue, Suite 200 , Seattle, WA 98121, United States
                Schools of Public Health and Earth and Biological Sciences, Loma Linda University , Loma Linda, CA 92350, United States
                Department of Fisheries and Wildlife, Michigan State University , East Lansing, MI 48824, United States
                Author notes
                Corresponding author. 5200 N. Lake Rd. Merced, CA 95343, United States; E-mail: cnaughton2@ 123456ucmerced.edu
                Author information
                https://orcid.org/0000-0002-3923-7465
                https://orcid.org/0000-0003-3142-6090
                https://orcid.org/0000-0002-1351-8963
                https://orcid.org/0000-0003-4360-2071
                Article
                xtad003
                10.1093/femsmc/xtad003
                10117741
                37333436
                6f673f7c-5409-48f4-b53f-9a749e8a80ad
                © The Author(s) 2023. Published by Oxford University Press on behalf of FEMS.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 June 2022
                : 16 December 2022
                : 11 January 2023
                : 21 February 2023
                Page count
                Pages: 8
                Funding
                Funded by: PATH, DOI 10.13039/100005624;
                Funded by: National Science Foundation, DOI 10.13039/100000001;
                Award ID: 2037834
                Award ID: 2027752
                Award ID: 2038087
                Categories
                Research Article
                Microbes & Disease
                AcademicSubjects/SCI01150

                geographic information systems (gis),wastewater-based epidemiology,sars-cov-2,open data,public health,covidpoops19 dashboard

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