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Background: Many respiratory viruses and their associated diseases are sensitive to meteorological factors. For SARS-CoV-2 and COVID-19, evidence on this sensitivity is inconsistent. Understanding the influence of meteorological factors on SARS-CoV-2 transmission and COVID-19 epidemiology can help to improve pandemic preparedness. Objectives: This review aimed to examine the recent evidence about the relation between meteorological factors and SARS-CoV-2/COVID-19. Methods: We conducted a global scoping review of peer-reviewed studies published from January 2020 up to January 2023 about the associations between temperature, solar radiation, precipitation, humidity, wind speed, and atmospheric pressure and SARS-CoV-2/COVID-19. Results: From 9,156 initial records, we included 474 relevant studies. Experimental studies on SARS-CoV-2 provided consistent evidence that higher temperatures and solar radiation negatively affect virus viability. Studies on COVID-19 (epidemiology) were mostly observational and provided less consistent evidence. Several studies considered interactions between meteorological factors or other variables such as demographics or air pollution. None of the publications included all determinants holistically. Discussion: The association between short-term meteorological factors and SARS-CoV-2/COVID-19 dynamics is complex. Interactions between environmental and social components need further consideration. A more integrated research approach can provide valuable insights to predict the dynamics of respiratory viruses with pandemic potential.

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Due to the impact respiratory viruses have on human health, a lot of data has been collected and visualised in tools such as dashboards that provide retrospective insights into the course of an epidemic or pandemic. Two well-known respiratory viruses, influenza virus and SARS-CoV-2, are the causative agents of influenza and COVID-19, respectively. A scoping review was performed using Embase including data from January 2000 until April 2021 to identify individual and environmental health parameters that affect transmission of influenza virus and SARS-CoV-2, as well as disease severity (morbidity (hospitalisation) and mortality) of influenza and COVID-19. Summary data was extracted from published articles. A total of 2280 unique articles were identified by the search, 484 articles were analysed, and 149 articles were included. The information of included articles was combined with data from Dutch databases to create prospective interactive maps that visualise risk areas in the Netherlands on health region, municipality, and neighbourhood-level. Included health parameters are contacts per day, mixing patterns, household composition, presence of certain indoor public spaces, urbanity, meteorological values, average income, age, ethnicity, comorbidity, sex, and smoking habits. The impact and input of these parameters are adjustable by users allowing a fit-for-purpose approach. These maps can be used to corroborate local policy decisions in times of health crisis, or in pandemic preparedness plans, serving as an instant visualisation tool of risk areas in the country. Despite limitations caused by data unavailability, simplification steps, and lack of validation, these interactive maps provide an important basis that can be elaborated on by further research that integrates both individual and environmental parameters.

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Legionnaires' disease (LD) is a severe pneumonia mainly caused by the bacterium Legionella pneumophila. Although many environmental sources of LD have been described, the sources of the majority of non-outbreak LD cases have not been identified. In several outbreaks in the Netherlands, wastewater treatment plants (WWTPs) were identified as the most likely source of infection. In this study, four criteria for Legionella growth and emission to air and surface waters were selected based on the literature and a risk matrix was drafted. An inventory was made of all WWTPs and their characteristics in the Netherlands. The risk matrix was applied to identify WWTPs at risk for Legionella growth and emission. Wastewater was collected at WWTPs with moderate to high risk for Legionella growth and emission. In 18% of the sampled WWTPs, Legionella spp. was detected using culture methods. The presented risk matrix can be used to assess the risks of Legionella growth and emission for WWTPs and support surveillance by prioritizing WWTPs. When Legionella is detected in the wastewater, it is recommended to take action to prevent emission to air or discharge on surface waters and, if possible, reduce the Legionella concentration.

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BACKGROUND: SARS-CoV-2 can be effectively transmitted between individuals located in close proximity to each other for extended durations. Aircraft provide such conditions. Although high attack rates during flights were reported, little was known about the risk levels of aerosol transmission of SARS-CoV-2 in aircraft cabins. OBJECTIVES: The major objective was to estimate the risk of contracting COVID-19 from transmission of aerosol particles in aircraft cabins. METHODS: In two single-aisle and one twin-aisle aircraft, dispersion of generated aerosol particles over a seven-row economy class cabin section was measured under cruise and taxi conditions and simulated with a computational fluid dynamic model under cruise conditions. Using the aerosol particle dispersion data, a quantitative microbial risk assessment was conducted for scenarios with an asymptomatic infectious person expelling aerosol particles by breathing and speaking. Effects of flight conditions were evaluated using generalized additive mixed models. RESULTS: Aerosol particle concentration decreased with increasing distance from the infectious person, and this decrease varied with direction. On a typical flight with an average shedder, estimated mean risk of contracting COVID-19 ranged from 1.3×10-3 to 9.0×10-2. Risk increased to 7.7×10-2 with a super shedder (<3% of cases) on a long flight. Risks increased with increasing flight duration: 2-23 cruise flights of typical duration and 2-10 flights of longer duration resulted in at least 1 case of COVID-19 due to onboard aerosol transmission by one average shedder, and in the case of one super shedder, at least 1 case in 1-3 flights of typical duration cruise and 1 flight of longer duration. DISCUSSION: Our findings indicate that the risk of contracting COVID-19 by aerosol transmission in an aircraft cabin is low, but it will not be zero. Testing before boarding may help reduce the chance of a (super)shedder boarding an aircraft and mask use further reduces aerosol transmission in the aircraft cabin. https://doi.org/10.1289/EHP11495.

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The Netherlands is one of the most densely populated countries in terms of people and livestock and is the second largest exporter of agricultural products worldwide. As a result, the Netherlands has a manure surplus. Excess application of manure can lead to environmental problems; therefore, manure needs to be treated and discharged. Manure can contain zoonotic pathogens, but whether exposure to manure and manure treatment also poses a risk to public health is still unknown. This study analysed the regulations, relevant actors, and responsibilities in the complex system of manure and public health in the Netherlands. Interviews and system mapping have demonstrated interlinkages between environmental, economic, and health aspects. Constraints and opportunities for public health protection have been identified. This study reveals the complexity of the Dutch manure policy, its scattered responsibilities, the challenge to deal with uncertainties, and, most importantly, the need for a microbial risk assessment in order to adequately communicate and manage possible risks to protect the health of animals, the environment, and people.

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BACKGROUND: Evidence for indoor airborne transmission of SARS-CoV-2 is accumulating. OBJECTIVES: We assessed of the risk of illness due to airborne SARS-CoV-2 particles from breathing, speaking, singing, coughing, and sneezing in indoor environments. METHODS: A risk assessment model, AirCoV2, for exposure to SARS-CoV-2 particles in aerosol droplets was developed. Previously published data on droplets expelled by breathing, speaking, singing, coughing, and sneezing by an infected person were used as inputs. Scenarios encompassed virus concentration, exposure time, and ventilation. Newly collected data of virus RNA copies in mucus from patients are presented. RESULTS: The expelled volume of aerosols was highest for a sneeze, followed by a cough, singing, speaking, and breathing. After 20 min of exposure, at 107 RNA copies/mL in mucus, all mean illness risks were largely estimated to be below 0.001, except for the "high" sneeze scenario. At virus concentrations above 108 RNA copies/mL, and after 2 h of exposure, in the high and "low" sneeze scenarios, the high cough scenario and the singing scenario, risks exceeded 0.01 and may become very high, whereas the low coughing scenario, the high and low speaking scenarios and the breathing scenario remained below 0.1. After 2 h of exposure, singing became the second highest risk scenario. One air exchange per hour reduced risk of illness by about a factor of 2. Six air exchanges per hour reduced risks of illness by a factor of 8-13 for the sneeze and cough scenarios and by a factor of 4-9 for the other scenarios. DISCUSSION: The large variation in the volume of expelled aerosols is discussed. The model calculations indicated that SARS-CoV-2 transmission via aerosols outside of the 1.5-m social distancing norm can occur. Virus concentrations in aerosols and/or the amount of expelled aerosol droplets need to be high for substantial transmission via this route. AirCoV2 is made available as interactive computational tool. https://doi.org/10.1289/EHP7886.

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Cryptosporidium is a leading cause of diarrhoea and infant mortality worldwide. A better understanding of the sources, fate and transport of Cryptosporidium via rivers is important for effective management of waterborne transmission, especially in the developing world. We present GloWPa-Crypto C1, the first global, spatially explicit model that computes Cryptosporidium concentrations in rivers, implemented on a 0.5 × 0.5° grid and monthly time step. To this end, we first modelled Cryptosporidium inputs to rivers from human faeces and animal manure. Next, we use modelled hydrology from a grid-based macroscale hydrological model (the Variable Infiltration Capacity model). Oocyst transport through the river network is modelled using a routing model, accounting for temperature- and solar radiation-dependent decay and sedimentation along the way. Monthly average oocyst concentrations are predicted to range from 10-6 to 102 oocysts L-1 in most places. Critical regions ('hotspots') with high concentrations include densely populated areas in India, China, Pakistan and Bangladesh, Nigeria, Algeria and South Africa, Mexico, Venezuela and some coastal areas of Brazil, several countries in Western and Eastern Europe (incl. The UK, Belgium and Macedonia), and the Middle East. Point sources (human faeces) appears to be a more dominant source of pollution than diffuse sources (mainly animal manure) in most world regions. Validation shows that GloWPa-Crypto medians are mostly within the range of observed concentrations. The model generally produces concentrations that are 1.5-2 log10 higher than the observations. This is likely predominantly due to the absence of recovery efficiency of the observations, which are therefore likely too low. Goodness of fit statistics are reasonable. Sensitivity analysis showed that the model is most sensitive to changes in input oocyst loads. GloWPa-Crypto C1 paves the way for many new opportunities at the global scale, including scenario analysis to investigate the impact of global change and management options on oocysts concentrations in rivers, and risk analysis to investigate human health risk.

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Understanding the environmental pathways of Cryptosporidium is essential for effective management of human and animal cryptosporidiosis. In this paper we aim to quantify livestock Cryptosporidium spp. loads to land on a global scale using spatially explicit process-based modeling, and to explore the effect of manure storage and treatment on oocyst loads using scenario analysis. Our model GloWPa-Crypto L1 calculates a total global Cryptosporidium spp. load from livestock manure of 3.2 × 1023 oocysts per year. Cattle, especially calves, are the largest contributors, followed by chickens and pigs. Spatial differences are linked to animal spatial distributions. North America, Europe, and Oceania together account for nearly a quarter of the total oocyst load, meaning that the developing world accounts for the largest share. GloWPa-Crypto L1 is most sensitive to oocyst excretion rates, due to large variation reported in literature. We compared the current situation to four alternative management scenarios. We find that although manure storage halves oocyst loads, manure treatment, especially of cattle manure and particularly at elevated temperatures, has a larger load reduction potential than manure storage (up to 4.6 log units). Regions with high reduction potential include India, Bangladesh, western Europe, China, several countries in Africa, and New Zealand.

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Cryptosporidium is a pathogenic protozoan parasite and is a leading cause of diarrhoea worldwide. The concentration of Cryptosporidium in the surface water is a determinant for probability of exposure and the risk of disease. Surface water concentrations are expected to change with population growth, urbanisation and changes in sanitation. The objective of this paper is to assess the importance of future changes in population, urbanisation and sanitation on global human emissions of Cryptosporidium to surface water. The GloWPa-Crypto H1 (the Global Waterborne Pathogen model for Human Cryptosporidium emissions version 1) model is presented and run for 2010 and with scenarios for 2050. The new scenarios are based on the Shared Socio-economic Pathways (SSPs) developed for the climate community. The scenarios comprise assumptions on sanitation changes in line with the storylines and population and urbanisation changes from the SSPs. In SSP1 population growth is limited, urbanisation large and sanitation and waste water treatment strongly improve. SSP1* is the same as SSP1, but waste water treatment does not improve. SSP3 sees large population growth, moderate urbanisation and sanitation and waste water treatment fractions that are the same as in 2010. Total global Cryptosporidium emissions to surface water for 2010 are estimated to be 1.6×1017 oocysts per year, with hotspots in the most urbanised parts of the world. In 2050 emissions are expected to decrease by 24% or increase by 52% and 70% for SSP1, SSP3 and SSP1* respectively. The emissions increase in all scenarios for countries in the Middle East and Africa (MAF) region, while emissions in large parts in Europe decrease in scenarios SSP1 and SSP3. Improving sanitation by connecting the population to sewers, should be combined with waste water treatment, otherwise (SSP1*) emissions in 2050 are expected to be much larger than in a situation with strong population growth and slow development of safe water and improved sanitation (SSP3). The results show that population increase, urbanisation and changes in sanitation should be considered when water quality and resulting health risks are estimated by water managers or public health specialists.

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The authors wish to make the following corrections to their paper [1].[...].

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Group A rotaviruses (RV) are the major cause of acute gastroenteritis in infants and young children globally. Waterborne transmission of RV and the presence of RV in water sources are of major public health importance. In this paper, we present the Global Waterborne Pathogen model for RV (GloWPa-Rota model) to estimate the global distribution of RV emissions to surface water. To our knowledge, this is the first model to do so. We review the literature to estimate three RV specific variables for the model: incidence, excretion rate and removal during wastewater treatment. We estimate total global RV emissions to be 2 × 1018 viral particles/grid/year, of which 87% is produced by the urban population. Hotspot regions with high RV emissions are urban areas in densely populated parts of the world, such as Bangladesh and Nigeria, while low emissions are found in rural areas in North Russia and the Australian desert. Even for industrialized regions with high population density and without tertiary treatment, such as the UK, substantial emissions are estimated. Modeling exercises like the one presented in this paper provide unique opportunities to further study these emissions to surface water, their sources and scenarios for improved management.