Assessment of Pathogens in Flood Waters in Coastal Rural Regions: Case study after Hurricane Michael and Florence

The severity of hurricanes, and thus the associated impacts, is changing over time. One of the understudied threats from damage caused by hurricanes is the potential for cross-contamination of water bodies with pathogens in coastal agricultural regions. Using microbiological data collected after hurricanes Florence and Michael, this study shows a dichotomy in the presence of pathogens in coastal North Carolina and Florida. Salmonella typhimurium was abundant in water samples collected in the regions dominated by swine farms. A drastic decrease in Enterococcus spp. in Carolinas is indicative of pathogen removal with flooding waters. Except for the abundance presence of Salmonella typhimurium, no significant changes in pathogens were observed after Hurricane Michael in the Florida panhandle. We argue that a comprehensive assessment of pathogens must be included in decision-making activities in the immediate aftermath of hurricanes to build resilience against risks of pathogenic exposure in rural agricultural and human populations in vulnerable locations

Geographical quantification of the seasonality of transmission of COVID19 in human population as a function of the variability of temperatures

Abstract Abstract Background The occurrence of cases of COVID-19 suggests that it will likely become seasonally endemic in human populations. Objectives We seek to provide a quantification of the seasonality of the occurrence and severity of COVID-19 cases in human populations. Methods Using global data, we show that the spatiotemporal distribution of COVID-19 cases is a function of distinct seasons and climates. We investigated this at the county and the country scale using a comparison of seasonal means, correlation analyses using ambient air temperatures and dew point temperatures, and multiple linear regression techniques. Results We found that most locations had the highest incidence of COVID-19 during winter compared to other seasons. Regions closer to the equator had a higher incidence of COVID-19 during the summer than regions further from the equator. Regions close to the equator, where mean annual temperatures have less variance compared to those further from the equator, had smaller differences between seasonal COVID-19 incidence. Correlation and regression analyses showed that ambient air and dew point temperatures were significantly associated with COVID-19 incidence. Discussion Our results suggest that temperature and the environment are influential factors to understand the transmission of COVID-19 within the human population. This research provides empirical evidence that temperature changes are a strong indicator of seasonal COVID-19 outbreaks, and as such it will aid in planning for future outbreaks and for mitigating their impacts

Distribution and Antibiotic Resistance Profiles of Salmonella enterica in Rural Areas of North Carolina After Hurricane Florence in 2018

The frequency and magnitude of extreme events are increasing globally (Arnell & Gosling, 2016). Inundation, as a result of massive flooding, has the potential to change environmental conditions abruptly, and as a result, add pressure to the metabolism and proliferation of microorganisms (Furtak et al., 2020). The resulting overland flows and additional burden from domestic sewer and septic tank systems during an extreme flood event can introduce pathogens into ecologically unstable water bodies. For example, Yu et al. (2018) reported elevated levels of Escherichia coli and antibiotic resistance genes (ARGs) in river water samples 6 months after flooding in Houston, TX. Rural counties in the United States also experience devastating effects of floods, including effects on agriculture and livestock production. These include loss of livestock, supply chain disruption, and the risk of contamination of the facilities housing agricultural animals (Bissett et al., 2018). Microbial contamination after a flood event needs to be investigated because floods may spread infectious diseases not only to livestock but also to humans as they interact with flooded waters

Carbon dioxide as an indicator of bioaerosol activity and human health in K-12 school systems: a scoping review of current knowledge

Indoor air quality (IAQ) in schools has received attention over the past decades but still lacks specific standards and regulations. This study aimed to review the impact of bioaerosol activity in indoor environments on acute respiratory diseases and explore whether carbon dioxide can be used as an indicator of bioaerosol and respiratory diseases in indoor environments in K-12 school systems. Findings suggest a lack of a consensual approach to evaluate bioaerosols impacting IAQ in indoor infrastructures, particularly in school environments; an elevated CO _2 concentration inside the school classrooms was not uncommon, and the evidence of unsatisfactory and degraded IAQ (surpassing ASHRAE standards) at public schools in rural and urban settings in one of the North Central County, Florida. It was found that CO _2 levels can be associated with bioaerosol activity, and sufficient ventilation within the space substantially reduces the airborne time of respiratory droplets and CO _2 levels. CO _2 monitoring can act as an effective, low-cost alternative to surveying or detecting the prevalence of respiratory diseases, which may hold strength through establishing critical CO _2 thresholds and, thereafter associating it with the infectious doses of pathogen activity

A Review of the Environmental Trigger and Transmission Components for Prediction of Cholera

Climate variables influence the occurrence, growth, and distribution of Vibrio cholerae in the aquatic environment. Together with socio-economic factors, these variables affect the incidence and intensity of cholera outbreaks. The current pandemic of cholera began in the 1960s, and millions of cholera cases are reported each year globally. Hence, cholera remains a significant health challenge, notably where human vulnerability intersects with changes in hydrological and environmental processes. Cholera outbreaks may be epidemic or endemic, the mode of which is governed by trigger and transmission components that control the outbreak and spread of the disease, respectively. Traditional cholera risk assessment models, namely compartmental susceptible-exposed-infected-recovered (SEIR) type models, have been used to determine the predictive spread of cholera through the fecal–oral route in human populations. However, these models often fail to capture modes of infection via indirect routes, such as pathogen movement in the environment and heterogeneities relevant to disease transmission. Conversely, other models that rely solely on variability of selected environmental factors (i.e., examine only triggers) have accomplished real-time outbreak prediction but fail to capture the transmission of cholera within impacted populations. Since the mode of cholera outbreaks can transition from epidemic to endemic, a comprehensive transmission model is needed to achieve timely and reliable prediction with respect to quantitative environmental risk. Here, we discuss progression of the trigger module associated with both epidemic and endemic cholera, in the context of the autochthonous aquatic nature of the causative agent of cholera, V. cholerae, as well as disease prediction.https://doi.org/10.3390/tropicalmed603014

Long-Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment

Diarrheal diseases, notably cholera, have been shown to be related to episodic seasonal variability in river discharge, predominantly low flows, in regions where water and sanitation infrastructure are inadequate. Forecasting river discharge in transboundary international basins a few months in advance remains elusive because the necessary geophysical data are unavailable or are not shared with stakeholders. We hypothesized that river discharge in large river basins is directly related to upstream water conditions that lead to generation of high and low flows. Using the Ganges-Brahmaputra-Meghna Rivers as an example and Bayesian regressive models, we showed that terrestrial water storage (TWS) anomalies from the Gravity Recovery and Climate Experiment (GRACE) can provide reliable estimates of flows, which are essential hydroclimatic variables for predicting endemic cholera, with an overall accuracy of 70% and up to 60 days in advance, without ancillary ground-based data

Local and Environmental Reservoirs of Salmonella enterica After Hurricane Florence Flooding

Abstract In many regions of the world, including the United States, human and animal fecal genetic markers have been found in flood waters. In this study, we use high‐resolution whole genomic sequencing to examine the origin and distribution of Salmonella enterica after the 2018 Hurricane Florence flooding. We specifically asked whether S. enterica isolated from water samples collected near swine farms in North Carolina shortly after Hurricane Florence had evidence of swine origin. To investigate this, we isolated and fully sequenced 18 independent S. enterica strains from 10 locations (five flooded and five unflooded). We found that all strains have extremely similar chromosomes with only five single nucleotide polymorphisms (SNPs) and possessed two plasmids assigned bioinformatically to the incompatibility groups IncFIB and IncFII. The chromosomal core genome and the IncFIB plasmid are most closely related to environmental Salmonella strains isolated previously from the southeastern US. In contrast, the IncFII plasmid was found in environmental S. enterica strains whose genomes were more divergent, suggesting the IncFII plasmid is more promiscuous than the IncFIB type. We identified 65 antibiotic resistance genes (ARGs) in each of our 18 S. enterica isolates. All ARGs were located on the Salmonella chromosome, similar to other previously characterized environmental isolates. All isolates with different SNPs were resistant to a panel of commonly used antibiotics. These results highlight the importance of environmental sources of antibiotic‐resistant S. enterica after extreme flood events

Asymmetric Relationship between Ambient Air Temperature and Incidence of COVID-19 in the Human Population

The complexity of transmission of COVID-19 in the human population cannot be overstated. Although major transmission routes of COVID-19 remain as human-to-human interactions, understanding the possible role of climatic and weather processes in accelerating such interactions is still a challenge. The majority of studies on the transmission of this disease have suggested a positive association between a decrease in ambient air temperature and an increase in human cases. Using data from 19 early epicenters, we show that the relationship between the incidence of COVID-19 and temperature is a complex function of prevailing climatic conditions influencing human behavior that govern virus transmission dynamics. We note that under a dry (low-moisture) environment, notably at dew point temperatures below 0 degrees C, the incidence of the disease was highest. Prevalence of the virus in the human population, when ambient air temperatures were higher than 24 degrees C or lower than 17 degrees C, was hypothesized to be a function of the interaction between humans and the built or ambient environment. An ambient air temperature range of 17 to 24 degrees C was identified, within which virus transmission appears to decrease, leading to a reduction in COVID-19 human cases

Predictive Intelligence for Cholera in Ukraine?

Cholera, an ancient waterborne diarrheal disease, remains a threat to public health, especially when climate/weather processes, microbiological parameters, and sociological determinants intersect with population vulnerabilities of loss of access to safe drinking water and sanitation infrastructure. The ongoing war in Ukraine has either damaged or severely crippled civil infrastructure, following which the human population is at risk of health disasters. This editorial highlights a perspective on using predictive intelligence to combat potential (and perhaps impending) cholera outbreaks in various regions of Ukraine. Reliable and judicious use of existing earth observations inspired mathematical algorithms integrating heuristic understanding of microbiological, sociological, and weather parameters have the potential to save or reduce the disease burden

Identification of Thresholds on Population Density for Understanding Transmission of COVID-19

Pathways of transmission of coronavirus (COVID-19) disease in the human population are still emerging. However, empirical observations suggest that dense human settlements are the most adversely impacted, corroborating a broad consensus that human-to-human transmission is a key mechanism for the rapid spread of this disease. Here, using logistic regression techniques, estimates of threshold levels of population density were computed corresponding to the incidence (case counts) in the human population. Regions with population densities greater than 3,000 person per square mile in the United States have about 95% likelihood to report 43,380 number of average cumulative cases of COVID-19. Since case numbers of COVID-19 dynamically changed each day until 30 November 2020, ca. 4% of US counties were at 50% or higher probability to 38,232 number of COVID-19 cases. While threshold on population density is not the sole indicator for predictability of coronavirus in human population, yet it is one of the key variables on understanding and rethinking human settlement in urban landscapes