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Elena N. Naumova   Dr.   
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Elena N. Naumova published an article in December 2018.
Top co-authors See all
Gagandeep Kang

359 shared publications

Christian Medical College, Vellore, India

Rajiv Sarkar

98 shared publications

Division of Gastrointestinal Sciences, Christian Medical College, Vellore, India

Patrick Webb

75 shared publications

United States Agency for International Development (USAID) Feed the Future Innovation Lab for Nutrition, Tufts University, Boston, Massachusetts

John L. Durant

65 shared publications

Department of Civil and Environmental Engineering, Tufts University School of Engineering, 200 College Ave, Medford, MA 02155, USA

Honorine Ward

50 shared publications

Division of Geographic Medicine and Infectious Diseases, Tufts Medical Center, Boston, Massachusetts, 02111, USA

161
Publications
7
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0
Downloads
461
Citations
Publication Record
Distribution of Articles published per year 
(2000 - 2018)
Total number of journals
published in
 
29
 
Publications See all
Article 0 Reads 0 Citations Cardiovascular Disease Hospitalizations in Louisiana Parishes’ Elderly before, during and after Hurricane Katrina Ninon A. Becquart, Elena N. Naumova, Gitanjali Singh, Kennet... Published: 28 December 2018
International Journal of Environmental Research and Public Health, doi: 10.3390/ijerph16010074
DOI See at publisher website ABS Show/hide abstract
The research on how health and health care disparities impact response to and recovery from a disaster, especially among diverse and underserved populations is in great need for a thorough evaluation. The time series analysis utilizing most complete national databases of medical records is an indispensable tool in assessing the destruction and health toll brought about by natural disasters. In this study, we demonstrated such an application by evaluating the impact of Hurricane Katrina in 2005 on cardiovascular disease (CVD), a primary cause of mortality among older adults that can be aggravated by natural disasters. We compared CVD hospitalizations before, during and after Katrina between white and black residents of three most populated parishes in Louisiana: Orleans and Jefferson, which were severely affected by the landfall and subsequent floods, and East Baton Rouge, which hosted many of the evacuees. We abstracted 383,552 CVD hospitalization records for Louisiana’s patients aged 65+ in 2005–2006 from the database maintained by the Center of Medicare & Medicaid Services. Daily time series of CVD-related hospitalization rates at each study parish were compiled, and the changes were characterized using segmented regression. In Orleans Parish, directly affected by the hurricane, hospitalization rates peaked on the 6th day after landfall with an increase (mean ± SD) from 7.25 ± 2.4 to 18.5 ± 17.3 cases/day per 10,000 adults aged 65+ (p < 0.001) and returned to pre-landfall level after ~2 months. Disparities in CVD rates between black and white older adults were exacerbated during and following landfall. In Orleans Parish, a week after landfall, the CVD rates increased to 26.3 ± 23.7 and 16.6 ± 11.7 cases/day per 10,000 people (p < 0.001) for black and white patients, respectively. The abrupt increase in CVDs is likely due to psychosocial and post-traumatic stress caused by the disaster and inadequate response. Inequities in resource allocation and access have to be addressed in disaster preparation and mitigation.
Article 0 Reads 0 Citations Plasma Response to Deuterium-Labeled Vitamin K Intake Varies by TG Response, but Not Age or Vitamin K Status, in Older a... Jessie L Ellis, Xueyan Fu, Ala Al Rajabi, Michael A Grusak, ... Published: 22 December 2018
The Journal of Nutrition, doi: 10.1093/jn/nxy216
DOI See at publisher website
Article 0 Reads 0 Citations Air pollution control and the occurrence of acute respiratory illness in school children of Quito, Ecuador Bertha Estrella, Fernando Sempértegui, Oscar H. Franco, Magd... Published: 30 October 2018
Journal of Public Health Policy, doi: 10.1057/s41271-018-0148-6
DOI See at publisher website ABS Show/hide abstract
Because of air quality management and control, traffic-related air pollution has declined in Quito, Ecuador. We evaluated the effect of a city-wide 5-year air pollution control program on the occurrence of acute respiratory illness (ARI). We compared two studies conducted at the same location in Quito: in 2000, 2 years before the policy to control vehicle emission was introduced, and in 2007. Each study involved ~ 730 children aged 6–12 years, observed for 15 weeks. We examined associations between carboxyhemoglobin (COHb) serum concentration—an exposure proxy for carbon monoxide (CO)—ambient CO, and ARI in both cohorts. In 2007, we found a 48% reduction in the ARI incidence (RR 0.52; 95% CI 0.45–0.62, p < 0.0001), and 92% decrease in the percentage of children with COHb > 2.5% as compared to the 2000 study. We found no association between COHb concentrations above the safe level of 2.5% and the ARI incidence (p = 0.736). The decline in air pollution due to vehicle emissions control was associated with a lower incidence of respiratory illness in school children.
Article 0 Reads 0 Citations The shift in seasonality of legionellosis in the USA T. M. Alarcon Falconi, M. S. Cruz, E. N. Naumova Published: 13 August 2018
Epidemiology and Infection, doi: 10.1017/s0950268818002182
DOI See at publisher website
Article 0 Reads 0 Citations Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and loca... Alexandra V Kulinkina, Yvonne Walz, Magaly Koch, Nana-Kwadwo... Published: 04 June 2018
PLOS Neglected Tropical Diseases,
PubMed View at PubMed ABS Show/hide abstract
Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance on surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.
Article 0 Reads 0 Citations Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and loca... Alexandra V. Kulinkina, Yvonne Walz, Magaly Koch, Nana-Kwadw... Published: 04 June 2018
PLOS Neglected Tropical Diseases, doi: 10.1371/journal.pntd.0006517
DOI See at publisher website ABS Show/hide abstract
Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10–30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure. Schistosomiasis is a water-related neglected tropical disease that disproportionately affects school-aged children in poor communities of low- and middle-income countries. Schistosomiasis transmission risk is affected by environmental, socioeconomic, and behavioral factors, including water, sanitation, and hygiene (WASH) conditions. We used fine spatial resolution (10–30 m) remotely sensed data, in combination with measures of local water access and groundwater quality, to predict schistosomiasis risk in 73 rural Ghanaian communities. We found that applying environmental models to specific locations where people contact surface water bodies (i.e., potential transmission locations), rather than to locations...
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