Dataset Information

Acquired insights from the long-term surveillance of SARS-CoV-2 RNA for COVID-19 monitoring: The case of Monterrey Metropolitan Area (Mexico).

ABSTRACT: Wastewater-based epidemiology offers a time- and cost-effective way to monitor SARS-CoV-2 spread in communities and therefore represents a complement to clinical testing. WBE applicability has been demonstrated in a number of cases over short-term periods as a method for tracking the prevalence of SARS-CoV-2 and an early-warning tool for predicting outbreaks in the population. This study reports SARS-CoV-2 viral loads from wastewater treatment plants (WWTPs) and hospitals over a 6-month period (June to December 2020). Results show that the overall range of viral load in positive tested samples was between 1.2 × 10³ and 3.5 × 10⁶ gene copies/l, unveiling that secondary-treated wastewaters mirrored the viral load of influents. The interpretation suggests that the viral titers found in three out of four WWTPs were associated to clinical COVID-19 surveillance indicators preceding 2-7 days the rise of reported clinical cases. The median wastewater detection rate of SARS-CoV-2 was one out of 14,300 reported new cases. Preliminary model estimates of prevalence ranged from 0.02 to 4.6% for the studied period. This comprehensive statistical and epidemiological analysis demonstrates that the applied wastewater-based approach to COVID-19 surveillance is in general consistent and feasible, although there is room for improvements.

SUBMITTER: Padilla-Reyes DA

PROVIDER: S-EPMC8853965 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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Acquired insights from the long-term surveillance of SARS-CoV-2 RNA for COVID-19 monitoring: The case of Monterrey Metropolitan Area (Mexico).

Padilla-Reyes Diego A DA Álvarez Mario Moises MM Mora Abrahan A Cervantes-Avilés Pabel A PA Kumar Manish M Loge Frank J FJ Mahlknecht Jürgen J

Environmental research 20220218

Wastewater-based epidemiology offers a time- and cost-effective way to monitor SARS-CoV-2 spread in communities and therefore represents a complement to clinical testing. WBE applicability has been demonstrated in a number of cases over short-term periods as a method for tracking the prevalence of SARS-CoV-2 and an early-warning tool for predicting outbreaks in the population. This study reports SARS-CoV-2 viral loads from wastewater treatment plants (WWTPs) and hospitals over a 6-month period ( ...[more]

PMID: 35189100

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Project description:Since starts the coronavirus disease 2019 (COVID-19) pandemic identified the presence of genomic fragments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in various environmental matrices: domestic sewage, surface waters, and contaminated freshwater. Environmental monitoring of SARS-CoV-2 is a tool for evaluating trend curves over the months, compared to several clinical cases of the disease. The objective of this study was to monitor the SARS-CoV-2 in environmental samples collected in different sites in a metropolitan area of Porto Alegre, Southern Brazil. During 10 months from 2020 to 2021, 300 samples were collected weekly and biweekly from nine points located in 3 cities: one point from a wastewater treatment plant (WWTP) in São Leopoldo (fortnightly collection), two points in Dilúvio Stream in Porto Alegre (fortnightly collection), two points in Pampa and Luiz Rau Streams (weekly collection), and two points in public fountains (fortnightly collection) in Novo Hamburgo. After collection, samples were concentrated by ultracentrifugation, and viral nucleic acids were extracted using MagMax® Core Nucleic Acid Purifications kits and submitted to RT-qPCR, using E, N1, and N2 gene targets of SARS-CoV-2. Only 7% (3/41) samples from public fountains were positive, with a mean viral load (VL) of SARS-CoV-2 RNA of 5.02 × 101 gc/l (2.41~8.59 × 101 gc/l), while the streams had average VL of 7.43 × 105 gc/l (Pampa), 7.06 × 105 gc/l (Luiz Rau), 2.01 × 105 gc/l (Dilúvio), and 4.46 × 105 cg/l (WWTP). The results showed varying levels of viral presence in different sample types, with a demonstrated correlation between environmental viral load and clinical COVID-19 cases. These findings contribute to understanding virus persistence and transmission pathways in the environment. Continuous monitoring, especially in less developed regions, is crucial for early detection of vaccine resistance, new variants, and potential COVID-19 resurgence.

Project description:Homicide is without doubt one of Mexico's most important security problems, with data showing that this dismal kind of violence sky-rocketed shortly after the war on drugs was declared in 2007. Since then, violent war-like zones have appeared and disappeared throughout Mexico, causing unfathomable human, social and economic losses. One of the most emblematic of these zones is the Monterrey metropolitan area (MMA), a central scenario in the narco-war. Being an important metropolitan area in Mexico and a business hub, MMA has counted hundreds to thousands of casualties. In spite of several approaches being developed to understand and analyze crime in general, and homicide in particular, the lack of accurate spatio-temporal homicide data results in incomplete descriptions. In order to describe the manner in which violence has evolved and spread in time and space through the city, here we propose a network-based approach. For this purpose, we define a homicide network where nodes are geographical entities that are connected through spatial and temporal relationships. We analyzed the time series of homicides in different municipalities and neighborhoods of the MMA, to observe whether or not a global correlation appeared. We studied the spatial correlation between neighborhoods where homicides took place, to observe whether distance is a factor of influence in the frequency of homicides. We constructed yearly co-occurrence networks, by correlating neighborhoods with homicides happening within a same week, and counting the co-occurrences of these neighborhood pairs in 1 year. We also constructed a crime network by aggregating all data of homicides, eliminating the temporal correlation, in order to observe whether homicide clusters appeared, and what those clusters were distributed geographically. Finally, we correlated the location and frequency of homicides with roads, freeways and highways, to observe if a trend in the homicidal violence appeared. Our network approach in the homicide evolution of MMA allows us to identify that (1) analyzing the whole 86-month period, we observed a correlation between close cities, which decreases in distant places. (2) at neighborhood level, correlations are not distance-dependent, on the contrary, highest co-occurrences appeared between distant neighborhoods and a polygon formed by close neighborhoods in downtown Monterrey. Moreover, (3) An elevated number of homicides occur close to the 85th freeway, which connects MMA with the US border. (4) Some socioeconomic barriers determine the presence of homicide violence. Finally, (5) we show a relation between homicidal crime and the urban landscape by studying the distance of safe and violent neighborhoods to the closest highway and by studying the evolution of highway and crime distance over the cartel-related years and the following period. With this approach, we are able to describe the spatial and temporal evolution of homicidal crime in a metropolitan area.

Dataset Information

Acquired insights from the long-term surveillance of SARS-CoV-2 RNA for COVID-19 monitoring: The case of Monterrey Metropolitan Area (Mexico).

Publications

Acquired insights from the long-term surveillance of SARS-CoV-2 RNA for COVID-19 monitoring: The case of Monterrey Metropolitan Area (Mexico).

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