Measuring Greenspace in Rural Areas for Studies of Birth Outcomes: A Comparison of Street View Data and Satellite Data.

Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes. Besides the direct measures of greenness, we also compared the measures of environmental diversity, calculated with the two types of data. Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye-level view largely reflects the immediate surroundings. Neither the street view data- nor the RS data-based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.

Greenspace and Land Cover Diversity During Pregnancy in a Rural Region, and Associations With Birth Outcomes.

Beneficial effects on health outcomes have been observed from exposure to spaces with substantial green vegetation ("greenspace"). This includes studies of greenspace exposure on birth outcomes; however, these have been conducted largely in urban regions. We characterized residential exposure to greenspace and land cover diversity during pregnancy in rural northern New England, USA, investigating whether variation in greenspace or diversity related to newborn outcomes. Five landscape variables (greenspace land cover, land cover diversity, impervious surface area, tree canopy cover, and the Normalized Difference Vegetation Index) were aggregated within six circular zones of radii from 100 to 3,000 m around residential addresses, and distance to conservation land was measured, providing a total of 31 greenspace and diversity metrics. Four birth outcomes along with potentially confounding variables were obtained from 1,440 participants in the New Hampshire Birth Cohort Study. Higher greenspace land cover up to 3,000 m was associated with larger newborn head circumference, while impervious surface area (non-greenspace) had the opposite association. Further, birth length was positively associated with land cover diversity. These findings support beneficial health impacts of greenspace exposure observed in urban regions for certain health outcomes, such as newborn head circumference and length but not others such as birthweight and gestational age. Further our results indicate that larger radius buffer zones may be needed to characterize the rural landscape. Vegetation indices may not be interchangeable with other greenspace metrics such as land cover and impervious surface area in rural landscapes.

Larval flushing alters malaria endemicity patterns in regions with similar habitat abundance.

A model of Anopheles gambiae populations dynamics coupled with Plasmodium falciparum transmission dynamics is extended to include mechanisms of larval flushing which are known to occur. Flushing dynamics are modeled using a simulation that incorporates seasonal, autocorrelated, and random components based on 30 years of rainfall data for the Kakamega District of the western Kenya highlands. The model demonstrates that flushing phenomena can account for differences between regions with the same annual larval habitat pattern, changing the World Health Organization endemicity classification from either hyperendemic or holoendemic to hypoendemic disease patterns. Mesoendemic patterns of infection occur at the boundary of the holoendemic to hypoendemic transition. For some levels of flushing the entomological inoculation rate drops to an insignificant amount and disease disappears, while the annual indoor resting density remains well above zero. In these scenarios, the disease is hypoendemic, yet the model shows that outbreaks can occur when disease is introduced at particular time points.

Modeling the Sensitivity of Blacklegged Ticks (Ixodes scapularis) to Temperature and Land Cover in the Northeastern United States.

The prevalence of Lyme disease and other tick-borne diseases is dramatically increasing across the United States. While the rapid rise in Lyme disease is clear, the causes of it are not. Modeling Ixodes scapularis Say (Acari: Ixodidae), the primary Lyme disease vector in the eastern United States, presents an opportunity to disentangle the drivers of increasing Lyme disease, including climate, land cover, and host populations. We improved upon a recently developed compartment model of ordinary differential equations that simulates I. scapularis growth, abundance, and infection with Borrelia burgdorferi (Spirochaetales: Spirochaetaceae) by adding land cover effects on host populations, refining the representation of growth stages, and evaluating output against observed data. We then applied this model to analyze the sensitivity of simulated I. scapularis dynamics across temperature and land cover in the northeastern United States. Specifically, we ran an ensemble of 232 simulations with temperature from Hanover, New Hampshire and Storrs, Connecticut, and land cover from Hanover and Cardigan in New Hampshire, and Windsor and Danielson in Connecticut. Consistent with observations, simulations of I. scapularis abundance are sensitive to temperature, with the warmer Storrs climate significantly increasing the number of questing I. scapularis at all growth stages. While there is some variation in modeled populations of I. scapularis infected with B. burgdorferi among land cover distributions, our analysis of I. scapularis response to land cover is limited by a lack of observations describing host populations, the proportion of hosts competent to serve as B. burgdorferi reservoirs, and I. scapularis abundance.

Mummified baboons reveal the far reach of early Egyptian mariners.

The Red Sea was witness to important events during human history, including the first long steps in a trade network (the spice route) that would drive maritime technology and shape geopolitical fortunes for thousands of years. Punt was a pivotal early node in the rise of this enterprise, serving as an important emporium for luxury goods, including sacred baboons (Papio hamadryas), but its location is disputed. Here, we use geospatial variation in the oxygen and strontium isotope ratios of 155 baboons from 77 locations to estimate the geoprovenance of mummified baboons recovered from ancient Egyptian temples and tombs. Five Ptolemaic specimens of P. anubis (404-40 BC) showed evidence of long-term residency in Egypt prior to mummification, consistent with a captive breeding program. Two New Kingdom specimens of P. hamadryas were sourced to a region that encompasses much of present-day Ethiopia, Eritrea, and Djibouti, and portions of Somalia and Yemen. This result is a testament to the tremendous reach of Egyptian seafaring during the 2nd millennium BC. It also corroborates the balance of scholarly conjecture on the location of Punt.

Strontium is a chemical element that can act as a geographic fingerprint: its composition differs between locations, and as it enters the food chain, it can help to retrace the life history of extant or past animals. In particular, strontium in teeth ­ which stop to develop early ­ can reveal where an individual was born; strontium in bone and hair, on the other hand, can show where it lived just before death. Together, these analyses may hold the key to archaeological mysteries, such as the location of a long-lost kingdom revered by ancient Egyptians. For hundreds of years, the Land of Punt was one of Egypt's strongest trading partners, and a place from which to import premium incense and prized monkeys. Travellers could reach Punt by venturing south and east of Egypt, suggesting that the kingdom occupied the southern Red Sea region. Yet its exact location is still highly debated. To investigate, Dominy et al. examined the mummies of baboons present in ancient Egyptian tombs, and compared the strontium compositions of the bones, hair and teeth of these remains with the ones found in baboons living in various regions across Africa. This shed a light on the origins of the ancient baboons: while some were probably raised in captivity in Egypt, others were born in modern Ethiopia, Eritrea, Djibouti, Somalia and Yemen ­ areas already highlighted as potential locations for the Land of Punt. The work by Dominy et al. helps to better understand the ancient trade routes that shaped geopolitical fortunes for millennia. It also highlights the need for further archaeological research in Eritrea and Somalia, two areas which are currently understudied.

Residential wood stove use and indoor exposure to PM2.5 and its components in Northern New England.

BACKGROUND: Residential wood stove use has become more prevalent in high-income countries, but only limited data exist on indoor exposure to PM2.5 and its components. METHODS: From 2014 to 2016, we collected 7-day indoor air samples in 137 homes of pregnant women in Northern New England, using a micro-environmental monitor. We examined associations of wood stove use with PM2.5 mass and its components [black carbon (BC), organic and elemental carbon and their fractions, and trace elements], adjusted for sampling season, community wood stove use, and indoor activities. We examined impact of stove age, EPA-certification, and wood moisture on indoor pollutants. RESULTS: Median (IQR) household PM2.5 was 6.65 (5.02) µg/m3 and BC was 0.23 (0.20) µg/m3. Thirty percent of homes used a wood stove during monitoring. In homes with versus without a stove, PM2.5 was 20.6% higher [although 95% confidence intervals (-10.6, 62.6) included the null] and BC was 61.5% higher (95% CI: 11.6, 133.6). Elemental carbon (total and fractions 3 and 4), potassium, calcium, and chloride were also higher in homes with a stove. Older stoves, non-EPA-certified stoves, and wet or mixed (versus dry) wood were associated with higher pollutant concentrations, especially BC. CONCLUSIONS: Homes with wood stoves, particularly those that were older and non-EPA-certified or burning wet wood had higher concentrations of indoor air combustion-related pollutants.

High-latitude warming initiated the onset of the last deglaciation in the tropics.

Atmospheric greenhouse gas concentrations are thought to have synchronized global temperatures during Pleistocene glacial-interglacial cycles, yet their impact relative to changes in high-latitude insolation and ice-sheet extent remains poorly constrained. Here, we use tropical glacial fluctuations to assess the timing of low-latitude temperature changes relative to global climate forcings. We report 10Be ages of moraines in tropical East Africa and South America and show that glaciers reached their maxima at ~29 to 20 ka, during the global Last Glacial Maximum. Tropical glacial recession was underway by 20 ka, before the rapid CO2 rise at ~18.2 ka. This "early" tropical warming was influenced by rising high-latitude insolation and coincident ice-sheet recession in both polar regions, which lowered the meridional thermal gradient and reduced tropical heat export to the high latitudes.

Effect of Rising Temperature on Lyme Disease: Ixodes scapularis Population Dynamics and Borrelia burgdorferi Transmission and Prevalence.

Warmer temperatures are expected to increase the incidence of Lyme disease through enhanced tick maturation rates and a longer season of transmission. In addition, there could be an increased risk of disease export because of infected mobile hosts, usually birds. A temperature-driven seasonal model of Borrelia burgdorferi (Lyme disease) transmission among four host types is constructed as a system of nonlinear ordinary differential equations. The model is developed and parametrized based on a collection of lab and field studies. The model is shown to produce biologically reasonable results for both the tick vector (Ixodes scapularis) and the hosts when compared to a different set of studies. The model is used to predict the response of Lyme disease risk to a mean annual temperature increase, based on current temperature cycles in Hanover, NH. Many of the risk measures suggested by the literature are shown to change with increased mean annual temperature. The most straightforward measure of disease risk is the abundance of infected questing ticks, averaged over a year. Compared to this measure, which is difficult and resource-intensive to track in the field, all other risk measures considered underestimate the rise of risk with rise in mean annual temperature. The measure coming closest was "degree days above zero." Disease prevalence in ticks and hosts showed less increase with rising temperature. Single field measurements at the height of transmission season did not show much change at all with rising temperature.

Modeling the Response of Anopheles gambiae (Diptera: Culicidae) Populations in the Kenya Highlands to a Rise in Mean Annual Temperature.

A dynamical model of Anopheles gambiae larval and adult populations is constructed that matches temperature-dependent maturation times and mortality measured experimentally as well as larval instar and adult mosquito emergence data from field studies in the Kenya Highlands. Spectral classification of high-resolution satellite imagery is used to estimate household density. Indoor resting densities collected over a period of one year combined with predictions of the dynamical model give estimates of both aquatic habitat and total adult mosquito densities. Temperature and precipitation patterns are derived from monthly records. Precipitation patterns are compared with average and extreme habitat estimates to estimate available aquatic habitat in an annual cycle. These estimates are coupled with the original model to produce estimates of adult and larval populations dependent on changing aquatic carrying capacity for larvae and changing maturation and mortality dependent on temperature. This paper offers a general method for estimating the total area of aquatic habitat in a given region, based on larval counts, emergence rates, indoor resting density data, and number of households.Altering the average daily temperature and the average daily rainfall simulates the effect of climate change on annual cycles of prevalence of An. gambiae adults. We show that small increases in average annual temperature have a large impact on adult mosquito density, whether measured at model equilibrium values for a single square meter of habitat or tracked over the course of a year of varying habitat availability and temperature.

A comparison of five malaria transmission models: benchmark tests and implications for disease control.

BACKGROUND: Models for malaria transmission are usually compared based on the quantities tracked, the form taken by each term in the equations, and the qualitative properties of the systems at equilibrium. Here five models are compared in detail in order to develop a set of performance measures that further illuminate the differences among models. METHODS: Five models of malaria transmission are compared. Parameters are adjusted to correspond to similar biological quantities across models. Nine choices of parameter sets/initial conditions are tested for all five models. The relationship between malaria incidence in humans and (1) malaria incidence in vectors, (2) man-biting rate, and (3) entomological inoculation rate (EIR) at equilibrium is tested for all models. A sensitivity analysis for all models is conducted at all parameter sets. Overall sensitivities are ranked for each of the five models. A set of simple control interventions is tested on two of the models. RESULTS: Four of these models behave consistently over a set of nine choices of parameters and initial conditions, with one behaving significantly differently. Two of the models do not match reported entomological inoculation rate data well. The sensitivity profiles, although consistently having similar top parameters, vary not only between models but among choices of parameters and initial conditions. A numerical experiment on two of the models illustrates the effect of these differences on control strategies, showing significant differences between models in predicting which of the control measures are more effective. CONCLUSIONS: A set of benchmark tests based on performance measures are developed to be used on any proposed malaria transmission model to test its overall behaviour in comparison to both other models and data sets.

Spatial analysis of amyotrophic lateral sclerosis in Northern New England, USA, 1997-2009.

INTRODUCTION: An environmental trigger of sporadic amyotrophic lateral sclerosis (ALS) is supported by geographic disparities in ALS incidence and development of the disease in conjugal couples. This study aims to investigate the incidence of ALS in the Northern New England states of New Hampshire (NH), Vermont (VT), and Maine (ME). METHODS: We reviewed medical records and community databases to identify dwelling addresses of 688 patients diagnosed with ALS in 1997-2009 in NH, VT, and ME. We used spatial analysis to identify clusters of census block groups with statistically significant high incidence. RESULTS: We identified 11 clusters of statistically significant high incidence, each containing 6 or more cases of ALS. These 11 clusters are grouped in 4 distinct regions. CONCLUSIONS: There appear to be areas of significant spatial clustering within Northern New England. Further analysis will be needed to confirm whether there is any correlation between these areas and potential environmental risk factors.

Spatial clustering of amyotrophic lateral sclerosis and the potential role of BMAA.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative syndrome which has no known cause, except for a small proportion of cases which are genetically inherited. The development of ALS likely involves both genetic and environmental risk factors. Environmental risk factors implicated in ALS have included heavy metals, trauma, pesticides, electrical injuries, electromagnetic radiation and the cyanobacterial-derived neurotoxin beta-N-methylamino-L-alanine (BMAA). To investigate possible environmental risks, a number of epidemiological studies of ALS have been conducted. Some of these studies employ spatial analysis techniques that examine for spatial clusters of ALS and can help guide further research into identifying environmental exposures. Despite identifying geographical disparities in the distribution of ALS cases, these studies have not provided any clear associations with environmental factors. We review the literature on important studies of spatial clustering of ALS and explore the hypothesized link between the neurotoxin BMAA and ALS.