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.

Changing climatic conditions influence parameters associated with the growth of pathogenic Vibrio spp. in the environment and, hence, are linked to increased incidence of vibriosis. Between 1992 and 2022, a long-term increase in Vibrio spp. infections was reported in Florida, USA. Furthermore, a spike in Vibrio spp. infections was reported post Hurricane Ian, a category five storm that made landfall in Florida on 28 September 2022. During October 2022, water and oyster samples were collected from three stations in Lee County in an area significantly impacted by Ian. Vibrio spp. were isolated, and whole-genome sequencing and phylogenetic analysis were done, with a focus on Vibrio parahaemolyticus and Vibrio vulnificus to provide genetic insight into pathogenic strains circulating in the environment. Metagenomic analysis of water samples provided insight with respect to human health-related factors, notably the detection of approximately 12 pathogenic Vibrio spp., virulence and antibiotic resistance genes, and mobile genetic elements, including the SXT/R391 family of integrative conjugative elements. Environmental parameters were monitored as part of a long-term time series analysis done using satellite remote sensing. In addition to anomalous rainfall and storm surge, changes in sea surface temperature and chlorophyll concentration during and after Ian favored the growth of Vibrio spp. In conclusion, genetic analysis coupled with environmental data and remote sensing provides useful public health information and, hence, constitute a valuable tool to proactively detect and characterize environmental pathogens, notably vibrios. These data can aid the development of early warning systems by yielding a larger source of information for public health during climate change. IMPORTANCE: Evidence suggests warming temperatures are associated with the spread of potentially pathogenic Vibrio spp. and the emergence of human disease globally. Following Hurricane Ian, the State of Florida reported a sharp increase in the number of reported Vibrio spp. infections and deaths. Hence, monitoring of pathogens, including vibrios, and environmental parameters influencing their occurrence is critical to public health. Here, DNA sequencing was used to investigate the genomic diversity of Vibrio parahaemolyticus and Vibrio vulnificus , both potential human pathogens, in Florida coastal waters post Hurricane Ian, in October 2022. Additionally, the microbial community of water samples was profiled to detect the presence of Vibrio spp. and other microorganisms (bacteria, fungi, protists, and viruses) present in the samples. Long-term environmental data analysis showed changes in environmental parameters during and after Ian were optimal for the growth of Vibrio spp. and related pathogens. Collectively, results will be used to develop predictive risk models during climate change.

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.

Intensification of smog episodes, following harvesting of paddy crops in agricultural plains of the Indus basin in the Indian subcontinent, are often attributed to farming practice of burning standing stubble during late autumn (October, November) months. Biomass burning (paddy stubble residual) is a preferred technique to clear farmlands for centuries by farmers in that basin. However, despite stable agricultural landholding and yield, smog is being increasingly associated with burning agricultural biomass, thus creating a paradox. Here, we show that the concentration of smog (NOx, PM_2.5, SO₂) in the ambient air exceeds the safe threshold limits throughout the entire year in the region. This study argues that agricultural biomass burning is an ephemeral event in the basin that may act as a catalyst to a deteriorated air quality in the entire region. Results further demonstrate that simultaneous saturation of air pollutants along with high ambient moisture content and low wind speeds following the monsoon season are strongly related to aggravated smog events. Findings from this study should help make holistic mitigation and intervention policies to monitor air quality for sustainability of public health in agricultural regions where farming activities are a dominant economic driver for society.

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.

In this study, water samples were analyzed from a rural area of North Carolina after Hurricane Florence in 2018 and the distribution of the ttrC virulence gene of Salmonella enterica were investigated. We also examined the distribution of culturable S. enterica and determined their antibiotic resistance profiles. Antibiotic resistance genes (ARGs) in the classes of aminoglycoside, beta‐lactam, and macrolide‐lincosamide‐streptogramin B (MLSB) were targeted in this study. The ttrC gene was detected in 23 out of 25 locations. There was a wider and higher range of the ttrC gene in flooded water versus unflooded water samples (0–2.12 × 10⁵ copies/L vs. 0–4.86 × 10⁴ copies/L). Culturable S. enterica was isolated from 10 of 25 sampling locations, which was less prevalent than the distribution of the ttrC gene. The antibiotic resistance profiles were not distinct among the S. enterica isolates. The aminoglycoside resistance gene aac(6')‐Iy had the highest relative abundance (around 0.05 copies/16S rRNA gene copy in all isolates) among all ARGs. These findings suggested that the 2018 flooding event led to higher copy numbers of the ttrC genes of S. enterica in some flooded water bodies compared to those in unflooded water bodies. The high ARG level and similar ARG profiles were observed in all S. enterica isolates from both flooded and unflooded samples, suggesting that the antibiotic resistance was prevalent in S. enterica within this region, regardless of flooding.