Identification of environmental, socioeconomic, water, sanitation, and hygiene (WaSH) factors associated with COVID-19 incidence in the Philippines: A nationwide modelling study.

Despite the implementation of non-pharmaceutical interventions, the threat of coronavirus disease 2019 (COVID-19) remains significant on a global scale. Identifying external factors contributing to its spread is crucial, especially given the World Health Organization's recommendation emphasizing access to water, sanitation, and hygiene as essential in curbing COVID-19. There is a notable discrepancy in access to sanitation facilities, particularly evident in low- and middle-income countries. However, there is a lack of quantitative assessments regarding these factors. This study examines various environmental, socioeconomic, water, sanitation, and hygiene factors and their associations with COVID-19 incidence. All regions in the Philippines were categorized into clusters based on socioeconomic factors. A conceptual structural equation model (SEM) was developed using domain knowledge. The best-fitting SEM for each cluster was determined, and associations between factors and COVID-19 incidence were estimated. The correlation analysis revealed that rainfall, minimum temperature, and relative humidity were positively correlated with weekly COVID-19 incidence in urban regions. Maximum temperature, mean temperature, wind speed, and wind direction were negatively correlated with weekly COVID-19 incidence in rural regions, with time lags of 0, 3, and 7 weeks. In urban regions (Cluster 1), factors such as urbanization rate (1.00), area (-0.93), and population (0.54) were found to be associated with weekly COVID-19 incidence. Conversely, in rural regions (Cluster 2), factors including area (0.17), basic sanitation (0.84), and wind direction (0.83) showed associations with weekly COVID-19 incidence. These factors were causally associated with a latent variable reflecting the hidden confounders associated with COVID-19 incidence. It is important to note that sanitation factors were associated only in rural regions. Improving access to sanitation facilities in rural regions of the Philippines is imperative to effectively mitigate disease transmission in future pandemics. Identification of the causal effect of unobserved confounders with COVID-19 incidence is recommended for future research.

Genetic diversity of murine norovirus populations less susceptible to chlorine.

High genetic diversity in RNA viruses contributes to their rapid adaptation to environmental stresses, including disinfection. Insufficient disinfection can occur because of the emergence of viruses that are less susceptible to disinfection. However, understanding regarding the mechanisms underlying the alteration of viral susceptibility to disinfectants is limited. Here, we performed an experimental adaptation of murine norovirus (MNV) using chlorine to understand the genetic characteristics of virus populations adapted to chlorine disinfection. Several MNV populations exposed to an initial free chlorine concentration of 50 ppm exhibited reduced susceptibility, particularly after the fifth and tenth passages. A dominant mutation identified using whole-genome sequencing did not explain the reduced susceptibility of the MNV populations to chlorine. Conversely, MNV populations with less susceptibility to chlorine, which appeared under higher chlorine stress, were accompanied by significantly lower synonymous nucleotide diversity (πS) in the major capsid protein (VP1). The nonsynonymous nucleotide diversity (πN) in VP1 in the less-susceptible populations was higher than that in the susceptible populations, although the difference was not significant. Therefore, the ability of MNV populations to adapt to chlorine was associated with the change in nucleotide diversity in VP1, which may lead to viral aggregate formation and reduction in chlorine exposure. Moreover, the appearance of some nonsynonymous mutations can also contribute to the alteration in chlorine susceptibility by influencing the efficiency of viral replication. This study highlights the importance of understanding the genetic characteristics of virus populations under disinfection, which can contribute to the development of effective disinfection strategies and prevent the development of virus populations less susceptible to disinfectants.

Sensitivity Evaluation of Enveloped and Non-enveloped Viruses to Ethanol Using Machine Learning: A Systematic Review.

Viral diseases are a severe public health issue worldwide. During the coronavirus pandemic, the use of alcohol-based sanitizers was recommended by WHO. Enveloped viruses are sensitive to ethanol, whereas non-enveloped viruses are considerably less sensitive. However, no quantitative analysis has been conducted to determine virus ethanol sensitivity and the important variables influencing the inactivation of viruses to ethanol. This study aimed to determine viruses' sensitivity to ethanol and the most important variables influencing the inactivation of viruses exposed to ethanol based on machine learning. We examined 37 peer-reviewed articles through a systematic search. Quantitative analysis was employed using a decision tree and random forest algorithms. Based on the decision tree, enveloped viruses required around ≥ 35% ethanol with an average contact time of at least 1 min, which reduced the average viral load by 4 log10. In non-enveloped viruses with and without organic matter, ≥ 77.50% and ≥ 65% ethanol with an extended contact time of ≥ 2 min were required for a 4 log10 viral reduction, respectively. Important variables were assessed using a random forest based on the percentage increases in mean square error (%IncMSE) and node purity (%IncNodePurity). Ethanol concentration was a more important variable with a higher %IncMSE and %IncNodePurity than contact time for the inactivation of enveloped and non-enveloped viruses with the available organic matter. Because specific guidelines for virus inactivation by ethanol are lacking, data analysis using machine learning is essential to gain insight from certain datasets. We provide new knowledge for determining guideline values related to the selection of ethanol concentration and contact time that effectively inactivate viruses.

Estimation of alkali dosage and contact time for treating human excreta containing viruses as an emergency response: a systematic review.

Water, sanitation, and hygiene provisions are essential during emergencies to prevent infectious disease outbreaks caused by improper human excreta management in settlements for people affected by natural disasters and conflicts. Human excreta disinfection is required when long-term containment in latrines is not feasible on-site. Alkali additives, including lime, are effective disinfectants for wastewater and faecal sludge containing large amounts of solid and dissolved organic matter. The aim of this study was to determine the minimum dose and contact time of alkali additives for treating virus-containing human excreta in emergency situations. We used literature data collected by searching Google Scholar and Web of Science. The date of the last search for each study was 31th May 2023. Only peer-reviewed articles that included disinfection practices in combination with quantitative data for the physicochemical data of a matrix and viral decay were selected for data extraction. Two reviewers independently collected data from each study. We extracted datasets from 14 studies that reported quantitative information about their disinfection tests, including viral decay over time, matrix types, and physicochemical properties. Three machine learning algorithms were applied to the collected dataset to determine the time required to achieve specified levels of virus inactivation under different environmental conditions. The best model was used to estimate the contact time to achieve a 3-log10 inactivation of RNA virus in wastewater and faeces. The most important variables for predicting the contact time were pH, temperature, and virus type. The estimated contact time for 3 log inactivation of RNA virus was <2 h at pH 12, which was achieved by adding 1.8 and 3.1% slaked lime to wastewater and faeces, respectively. The contact time decreased exponentially with the pH of the sludge and wastewater. In contrast, the pH of the sludge and wastewater increased linearly with the slaked lime dosage. Lime treatment is a promising measure where long-term containment in latrine is not feasible in densely populated areas, as 1 day is sufficient to inactivate viruses. The relationship we have identified between required contact time and lime dosage is useful for practitioners in determining appropriate treatment conditions of human waste.

Decay rate estimation of respiratory viruses in aerosols and on surfaces under different environmental conditions.

Majority of the viral outbreaks are super-spreading events established within 2-10 h, dependent on a critical time interval for successful transmission between humans, which is governed by the decay rates of viruses. To evaluate the decay rates of respiratory viruses over a short span, we calculated their decay rate values for various surfaces and aerosols. We applied Bayesian regression and ridge regression and determined the best estimation for respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), severe acute respiratory syndrome coronavirus (SARS-CoV), middle east respiratory syndrome coronavirus (MERS-CoV), influenza viruses, and respiratory syncytial virus (RSV); the decay rate values in aerosols for these viruses were 4.83 ± 5.70, 0.40 ± 0.24, 0.11 ± 0.04, 2.43 ± 5.94, and 1.00 ± 0.50 h-1, respectively. The highest decay rate values for each virus type differed according to the surface type. According to the model performance criteria, the Bayesian regression model was better for SARS-CoV-2 and influenza viruses, whereas ridge regression was better for SARS-CoV and MERS-CoV. A simulation using a better estimation will help us find effective non-pharmaceutical interventions to control virus transmissions.

COVID-19 case prediction via wastewater surveillance in a low-prevalence urban community: a modeling approach.

Estimating and predicting the epidemic size from wastewater surveillance results remains challenging for the practical implementation of wastewater-based epidemiology (WBE). In this study, by employing a highly sensitive detection method, we documented the time series of SARS-CoV-2 RNA occurrence in the wastewater influent from an urban community with a 360,000 population in Japan, from August 2020 to February 2021. The detection frequency of the viral RNA increased during the outbreak events of COVID-19 and the highest viral RNA concentration was recorded at the beginning of January 2021, amid the most serious outbreak event during the study period. We found that: (1) direct back-calculation still suffers from great uncertainty dominated by inconsistent detection and the varying gap between the observed wastewater viral load and the estimated patient viral load, and (2) the detection frequency correlated well with reported cases and the prediction of the latter can be carried out via data-driven modeling methods. Our results indicate that wastewater virus occurrence can contribute to epidemic surveillance in ways more than back-calculation, which may spawn future wastewater surveillance implementations.

Experimental Adaptation of Murine Norovirus to Calcium Hydroxide.

Slaked lime (calcium hydroxide) is a commonly used disinfectant for fecal sludge. Although viruses are inactivated by lime treatment, whether RNA viruses adapt to lime treatment has not yet been determined. Here, we show that murine norovirus developed higher tolerance during serial passages with lime treatment. We compared synonymous and non-synonymous nucleotide diversities of the three open reading frames of viral genome and revealed that virus populations were subjected to enhanced purifying selection over the course of serial passages with lime treatment. Virus adaptation to lime treatment was coincident with amino acid substitution of lysine to arginine at position 345 (K345R) on the major capsid protein VP1, which accounted for more than 90% of the population. The infectious clones with the K345R produced using a plasmid-based reverse genetics system exhibited greater tolerance in a lime solution, which indicated that the specific amino acid substitution was solely involved in the viral tolerance in lime treatment.

Comparison of five polyethylene glycol precipitation procedures for the RT-qPCR based recovery of murine hepatitis virus, bacteriophage phi6, and pepper mild mottle virus as a surrogate for SARS-CoV-2 from wastewater.

Polyethylene glycol (PEG) precipitation is one of the conventional methods for virus concentration. This technique has been used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. The procedures and seeded surrogate viruses were different among implementers; thus, the reported whole process recovery efficiencies considerably varied among studies. The present study compared five PEG precipitation procedures, with different operational parameters, for the RT-qPCR-based whole process recovery efficiency of murine hepatitis virus (MHV), bacteriophage phi6, and pepper mild mottle virus (PMMoV), and molecular process recovery efficiency of murine norovirus using 34 raw wastewater samples collected in Japan. The five procedures yielded significantly different whole process recovery efficiency of MHV (0.070%-2.6%) and phi6 (0.071%-0.51%). The observed concentration of indigenous PMMoV ranged from 8.9 to 9.7 log (8.2 × 108 to 5.6 × 109) copies/L. Interestingly, PEG precipitation with 2-h incubation outperformed that with overnight incubation partially due to the difference in molecular process recovery efficiency. The recovery load of MHV exhibited a positive correlation (r = 0.70) with that of PMMoV, suggesting that PMMoV is the potential indicator of the recovery efficiency of SARS-CoV-2. In addition, we reviewed 13 published studies and found considerable variability between different studies in the whole process recovery efficiency of enveloped viruses by PEG precipitation. This was due to the differences in operational parameters and surrogate viruses as well as the differences in wastewater quality and bias in the measurement of the seeded load of surrogate viruses, resulting from the use of different analytes and RNA extraction methods. Overall, the operational parameters (e.g., incubation time and pretreatment) should be optimized for PEG precipitation. Co-quantification of PMMoV may allow for the normalization of SARS-CoV-2 RNA concentration by correcting for the differences in whole process recovery efficiency and fecal load among samples.

Hierarchical Bayesian modeling for predictive environmental microbiology toward a safe use of human excreta: Systematic review and meta-analysis.

The pathogen concentration in human excreta needs to be managed appropriately, but a predictive approach has yet to be implemented due to a lack of kinetics models for pathogen inactivation that are available under varied environmental conditions. Our goals were to develop inactivation kinetics models of microorganisms applicable under varied environmental conditions of excreta matrices and to identify the appropriate indicators that can be monitored during disinfection processes. We conducted a systematic review targeting previous studies that presented time-course decay of a microorganism and environmental conditions of matrices. Defined as a function of measurable factors including treatment time, pH, temperature, ammonia concentration and moisture content, the kinetic model parameters were statistically estimated using hierarchical Bayesian modeling. The inactivation kinetics models were constructed for Escherichia coli, Salmonella, Enterococcus, Ascaris eggs, bacteriophage MS2, enterobacteria phage phiX174 and adenovirus. The inactivation rates of a microorganism were predicted using the established model. Ascaris eggs were identified as the most tolerant microorganisms, followed by bacteriophage MS2 and Enterococcus. Ammonia concentration, temperature and moisture content were the critical factors for the Ascaris inactivation. Our model predictions coincided with the current WHO guidelines. The developed inactivation kinetics models enable us to predict microbial concentration in excreta matrices under varied environmental conditions, which is essential for microbiological risk management in emerging resource recovery practices from human excreta.

Early warning of COVID-19 via wastewater-based epidemiology: potential and bottlenecks.

An effective early warning tool is of great administrative and social significance to the containment and control of an epidemic. Facing the unprecedented global public health crisis caused by COVID-19, wastewater-based epidemiology (WBE) has been given high expectations as a promising surveillance complement to clinical testing which had been plagued by limited capacity and turnaround time. In particular, recent studies have highlighted the role WBE may play in being a part of the early warning system. In this study, we briefly discussed the basics of the concept, the benefits and critical points of such an application, the challenges faced by the scientific community, the progress made so far, and what awaits to be addressed by future studies to make the concept work. We identified that the shedding dynamics of infected individuals, especially in the form of a mathematical shedding model, and the back-calculation of the number of active shedders from observed viral load are the major bottlenecks of WBE application in the COVID-19 pandemic that deserve more attention, and the sampling strategy (location, timing, and interval) needs to be optimized to fit the purpose and scope of the WBE project.

Viral Interference as a Factor of False-Negative in the Infectious Adenovirus Detection Using Integrated Cell Culture-PCR with a BGM Cell Line.

This study investigated the influence of viral interference on the detection of enteric viruses using the integrated cell culture (ICC)-PCR with a BGM cell line. It was possible to detect 102 plaque-forming units (PFU)/flask of enterovirus 71 (EV71) in spite of the presence of 104 PFU/flask of adenovirus 40 (AdV40). Meanwhile, 104 PFU/flask of AdV40 was not detected in the presence of 102 PFU/flask of EV71. This inhibition of AdV40 detection using ICC-PCR was attributable to the growth of EV71, because the addition of a growth inhibitor of EV71 (rupintrivir) neutralized the detection inhibition of AdV40. The growth inhibition of AdV40 under co-infection with EV71 is probably caused by the immune responses of EV71-infected cells. AdV is frequently used as a fecal contamination indicator of environmental water, but this study demonstrated that false-negative detection of infectious AdV using ICC-PCR could be caused by the co-existence of infectious EV in a water sample. The addition of rupintrivir could prevent false-negative detection of AdV using ICC-PCR. This study, therefore, emphasizes the importance of confirming the presence of multiple enteric viruses in a sample derived from environmental water prior to the application of ICC-PCR because the viral interference phenomenon may lead to the false-negative detection of target viruses.

Inactivation kinetics modeling of Escherichia coli in concentrated urine for implementing predictive environmental microbiology in sanitation safety planning.

Urine concentration (condensation) leads to the inactivation of pathogens in urine owing to a hyperosmotic environment. This study proposed an inactivation kinetic model of Escherichia coli (E. coli), a surrogate of human bacterial pathogens, in concentrated synthetic urine. The model parameters were obtained under an assumption that the inactivation rate of E. coli followed a binomial distribution, which made it possible to accurately simulate the time-course decay of E. coli in synthetic urine. The inactivation rate constant values obtained in concentrated urine samples, ammonium buffer solutions and carbonate buffer solutions indicated that the osmotic pressure was a relatively predominant cause for the inactivation of E. coli. The appropriate storage time was estimated using the approach of quantitative microbial risk assessment, which indicated that the 5-fold concentrated urine could be safely collected after 1-day storage when urea was hydrolyzed, whereas 91-hour storage was required for non-concentrated urine. The occupational risk was not negligible even with 6-month storage at 20 °C when urea was not hydrolyzed, which suggested that the urine storage styles should be clarified more minutely. The present study highlights the importance of "predictive environmental microbiology," which deals with inactivation kinetic models of microorganisms under varied environmental conditions to fully implement the hazard analysis and critical control point (HACCP) approach for the safe use of human excreta in agriculture.

Optically Active Helical Lanthanide Complexes: Storable Chiral Lewis Acidic Catalysts for Enantioselective Diels-Alder Reaction of Siloxydienes.

Lanthanide triflates and a series of hexadentate chiral ligand complexes were synthesized. X-ray-quality crystals were obtained from mixtures of the lanthanide complexes, which were helical in shape. The complexes showed Lewis acidity and catalyzed the enantioselective Diels-Alder reaction of electron-rich siloxydienes. The complexes were stable enough to be stored at ambient temperature on a laboratory bench and retained their Lewis acidity even after a month.

Sign-constrained linear regression for prediction of microbe concentration based on water quality datasets.

This study presents a novel methodology for estimating the concentration of environmental pollutants in water, such as pathogens, based on environmental parameters. The scientific uniqueness of this study is the prevention of excess conformity in the model fitting by applying domain knowledge, which is the accumulated scientific knowledge regarding the correlations between response and explanatory variables. Sign constraints were used to express domain knowledge, and the effect of the sign constraints on the prediction performance using censored datasets was investigated. As a result, we confirmed that sign constraints made prediction more accurate compared to conventional sign-free approaches. The most remarkable technical contribution of this study is the finding that the sign constraints can be incorporated in the estimation of the correlation coefficient in Tobit analysis. We developed effective and numerically stable algorithms for fitting a model to datasets under the sign constraints. This novel algorithm is applicable to a wide variety of the prediction of pollutant contamination level, including the pathogen concentrations in water.

Identification of the inactivating factors and mechanisms exerted on MS2 coliphage in concentrated synthetic urine.

Volume reduction (condensation) is a key for the practical usage of human urine as a fertilizer because it enables the saving of storage space and the reduction of transportation cost. However, concentrated urine may carry infectious disease risks resulting from human pathogens frequently present in excreta, though the survival of pathogens in concentrated urine is not well understood. In this study, the inactivation of MS2 coliphage, a surrogate for single-stranded RNA human enteric viruses, in concentrated synthetic urine was investigated. The infectious titer reduction of MS2 coliphage in synthetic urine samples was measured by plaque assay, and the reduction of genome copy number was monitored by reverse transcription-quantitative PCR (RTqPCR). Among chemical-physical conditions such as pH and osmotic pressure, uncharged ammonia was shown to be the predominant factor responsible for MS2 inactivation, independently of urine concentration level. The reduction rate of the viral genome number varied among genome regions, but the comprehensive reduction rate of six genome regions was well correlated with that of the infectious titer of MS2 coliphage. This indicates that genome degradation is the main mechanism driving loss of infectivity, and that RT-qPCR targeting the six genome regions can be used as a culture-independent assay for monitoring infectivity loss of the coliphage in urine. MS2 inactivation rate constants were well predicted by a model using ion composition and speciation in synthetic urine samples, which suggests that MS2 infectivity loss can be estimated solely based on the solution composition, temperature and pH, without explicitly accounting for effects of osmotic pressure.