Connectivity sustains disease transmission in environments with low potential for endemicity: modelling schistosomiasis with hydrologic and social connectivities

Social interaction and physical interconnections between populations can influence the spread of parasites. The role that these pathways play in sustaining the transmission of parasitic diseases is unclear, although increasingly realistic metapopulation models are being used to study how diseases persist in connected environments. We use a mathematical model of schistosomiasis transmission for a distributed set of heterogeneous villages to show that the transport of parasites via social (host movement) and environmental (parasite larvae movement) pathways has consequences for parasite control, spread and persistence. We find that transmission can be sustained regionally throughout a group of connected villages even when individual village conditions appear not to support endemicity. Optimum transmission is determined by an interplay between different transport pathways, and not necessarily by those that are the most dispersive (e.g. disperse social contacts may not be optimal for transmission). We show that the traditional targeting of villages with high infection, without regard to village interconnections, may not lead to optimum control. These findings have major implications for effective disease control, which needs to go beyond considering local variations in disease intensity, to also consider the degree to which populations are interconnected

Does surrounding greenness moderate the relationship between apparent temperature and physical activity? Findings from the PHENOTYPE project

Background: Physical activity can be affected by both meteorological conditions and surrounding greenness, but few studies have evaluated the effects of these environmental factors on physical activity simultaneously. This multi-city comparative study aimed to assess the synergetic effects of apparent temperature and surrounding greenness on physical activity in four European cities. Specifically, we aimed to identify an interaction between surrounding greenness and apparent temperature in the effects on physical activity. Methods: Data were collected from 352 adult residents of Barcelona (Spain), Stoke-on-Trent (United Kingdom), Doetinchem (The Netherlands), and Kaunas (Lithuania) as part of the PHENOTYPE study. Participants wore a smartphone for seven consecutive days between May-December 2013 and provided additional sociodemographic survey data. Hourly average physical activity (Metabolic Equivalent of Task (MET)) and surrounding greenness (NDVI) were derived from the Calfit mobile application collecting accelerometer and location data. Hourly apparent temperature was calculated from temperature and relative humidity, which were obtained from local meteorological stations along with other meteorological covariates (rainfall, windspeed, and sky darkness). We assessed the interaction effects of apparent temperature and surrounding greenness on hourly physical activity for each city using linear mixed models, while adjusting for meteorological, demographic, and time-related variables. Results: We found significant interactions between apparent temperature and surrounding greenness on hourly physical activity in all four cities. Significant quadratic effects of apparent temperature were found in the highest level of surrounding greenness for Stoke-on-Trent and Doetinchem, with 4% decrease in median MET observed for a 10°C departure from optimal temperature (15.2°C and 14.6°C, respectively). On the other hand, significant linear effects were found for higher levels of surrounding greenness in Barcelona and Kaunas, whereby an increase of 10°C was associated with ∼4% increase in median MET. Conclusion: Apparent temperature and surrounding greenness interacted in the effect on hourly physical activity across the four European cities, with varying effect between cities. While quadratic effects of temperature suggest diminishing levels of physical activity in the highest greenness levels in cities of temperate climates, the variation in surrounding greenness between cities could be further explored, particularly by looking at indoor-outdoor locations. The study findings support the need for evidence-based physical activity promotion and urban design

The use of a vest equipped with a global positioning system to assess water-contact patterns associated with schistosomiasis

The real exposure to many of the tropical diseases is difficult to assess at the individual-level due to problems of recall, self-reported diaries, personnel requirements, and altered behaviour related to observation. We present a study in an area endemic for Schistosoma japonicum in which global positioning system (GPS) receivers were used for personal time-activity monitoring to assess water-contact associated with schistosomiasis transmission. The study subjects were equipped with a vest with an embedded GPS receiver for 8-hour periods. The resulting data were used to create hourly time-activity maps, which were subsequently used in interviews to ascertain the timing and location of the water-contacts. Based on a sample of twenty-four 8-hour person-days we found that individuals averaged 1.4 ± 1.2 water-contacts per day, and were surprisingly mobile, with 39% of the participants having spent time out of the village (0.8 ± 1.4 hours outside of village). Such mobility suggests the need for further research into social patterns that may facilitate the spread of parasites, and contribute to sustained transmission. We present an assessment of the accuracy of cheaper commercially- available GPS units that have shown promise in such applications. We feel that a speed-filtering method is effective in managing measurement errors commonly encountered during personal activity monitoring with GPS. We conclude that personal GPS units can help reduce recall problems associated with other methods of assessing water-contact, and that they offer valuable insights into time-activity patterns that influence schistosomiasis transmission

Strategies to Reduce Person-to-Person Transmission during Widespread Escherichia coli O157:H7 Outbreak

During the Escherichia coli O157:H7 outbreak in 2006 in the United States, the primary strategy to prevent illness was to advise consumers not to eat spinach. No widespread warnings were issued about preventing person-to-person (secondary) transmission. A disease transmission model, fitted to the current data, was used to investigate likely reductions in illnesses that could result from interventions to prevent secondary transmission. The model indicates that exposure to contaminated spinach occurred early in the outbreak and that the secondary illness transmission was similar to that in previous E. coli outbreaks (≈12%). The model also suggests that even a modestly effective strategy to interrupt secondary transmission (prevention of only 2%–3% of secondary illnesses) could result in a reduction of ≈5%–11% of symptomatic cases. This analysis supports the use of widespread public health messages during outbreaks of E. coli O157:H7 with specific advice on how to interrupt secondary transmission

Assessment of traffic-related noise in three cities in the United States

BACKGROUND: Traffic-related noise is a growing public health concern in developing and developed countries due to increasing vehicle traffic. Epidemiological studies have reported associations between noise exposure and high blood pressure, increased risk of hypertension and heart disease, and stress induced by sleep disturbance and annoyance. These findings motivate the need for regular noise assessments within urban areas. This paper assesses the relationships between traffic and noise in three US cities. METHODS: Noise measurements were conducted in downtown areas in three cities in the United States: Atlanta, Los Angeles, and New York City. For each city, we measured ambient noise levels, and assessed their correlation with simultaneously measured vehicle counts, and with traffic data provided by local Metropolitan Planning Organizations (MPO). Additionally, measured noise levels were compared to noise levels predicted by the Federal Highway Administration’s Traffic Noise Model using (1) simultaneously measured traffic counts or (2) MPO traffic data sources as model input. RESULTS: We found substantial variations in traffic and noise within and between cities. Total number of vehicle counts explained a substantial amount of variation in measured ambient noise in Atlanta (78%), Los Angeles (58%), and New York City (62%). Modeled noise levels were moderately correlated with measured noise levels when observed traffic counts were used as model input. Weaker correlations were found when MPO traffic data was used as model input. CONCLUSIONS: Ambient noise levels measured in all three cities were correlated with traffic data, highlighting the importance of traffic planning in mitigating noise-related health effects. Model performance was sensitive to the traffic data used as input. Future noise studies that use modeled noise estimates should evaluate traffic data quality and should ideally include other factors, such as local roadway, building, and meteorological characteristics