Trends and patterns of disparities in diabetes and chronic kidney disease mortality among US counties, 1980-2014.

INTRODUCTION: Diabetes and chronic kidney diseases are associated with a large health burden in the USA and globally. OBJECTIVE: To estimate age-standardized mortality rates by county from diabetes mellitus and chronic kidney disease. DESIGN AND SETTING: Validated small area estimation models were applied to de-identified death records from the National Center for Health Statistics (NCHS) and population counts from the census bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 from diabetes mellitus and chronic kidney disease (CKD). EXPOSURES: County of residence. MAIN OUTCOMES AND MEASURES: Age-standardized mortality rates by county, year, sex, and cause. RESULTS: Between 1980 and 2014, 2,067,805 deaths due to diabetes were recorded in the USA. The mortality rate due to diabetes increased by 33.6% (95% UI: 26.5%-41.3%) between 1980 and 2000 and then declined by 26.4% (95% UI: 22.8%-30.0%) between 2000 and 2014. Counties with very high mortality rates were found along the southern half of the Mississippi river and in parts of South and North Dakota, while very low rates were observed in central Colorado, and select counties in the Midwest, California, and southern Florida. A total of 1,659,045 deaths due to CKD were recorded between 1980 and 2014 (477,332 due to diabetes mellitus, 1,056,150 due to hypertension, 122,795 due to glomerulonephritis, and 2,768 due to other causes). CKD mortality varied among counties with very low mortality rates observed in central Colorado as well as some counties in southern Florida, California, and Great Plains states. High mortality rates from CKD were observed in counties throughout much of the Deep South, and a cluster of counties with particularly high rates was observed around the Mississippi river. CONCLUSIONS AND RELEVANCE: This study found large inequalities in diabetes and CKD mortality among US counties. The findings provide insights into the root causes of this variation and call for improvements in risk factors, access to medical care, and quality of medical care.

Predicting the environmental suitability for onchocerciasis in Africa as an aid to elimination planning.

Recent evidence suggests that, in some foci, elimination of onchocerciasis from Africa may be feasible with mass drug administration (MDA) of ivermectin. To achieve continental elimination of transmission, mapping surveys will need to be conducted across all implementation units (IUs) for which endemicity status is currently unknown. Using boosted regression tree models with optimised hyperparameter selection, we estimated environmental suitability for onchocerciasis at the 5 × 5-km resolution across Africa. In order to classify IUs that include locations that are environmentally suitable, we used receiver operating characteristic (ROC) analysis to identify an optimal threshold for suitability concordant with locations where onchocerciasis has been previously detected. This threshold value was then used to classify IUs (more suitable or less suitable) based on the location within the IU with the largest mean prediction. Mean estimates of environmental suitability suggest large areas across West and Central Africa, as well as focal areas of East Africa, are suitable for onchocerciasis transmission, consistent with the presence of current control and elimination of transmission efforts. The ROC analysis identified a mean environmental suitability index of 0·71 as a threshold to classify based on the location with the largest mean prediction within the IU. Of the IUs considered for mapping surveys, 50·2% exceed this threshold for suitability in at least one 5 × 5-km location. The formidable scale of data collection required to map onchocerciasis endemicity across the African continent presents an opportunity to use spatial data to identify areas likely to be suitable for onchocerciasis transmission. National onchocerciasis elimination programmes may wish to consider prioritising these IUs for mapping surveys as human resources, laboratory capacity, and programmatic schedules may constrain survey implementation, and possibly delaying MDA initiation in areas that would ultimately qualify.

Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability.

BACKGROUND: Rift Valley Fever (RVF) poses a threat to human and animal health throughout much of Africa and the Middle East and has been recognized as a global health security priority and a key preparedness target. METHODS: We combined RVF occurrence data from a systematic literature review with animal notification data from an online database. Using boosted regression trees, we made monthly environmental suitability predictions from January 1995 to December 2016 at a 5 × 5-km resolution throughout regions of Africa, Europe, and the Middle East. We calculated the average number of months per year suitable for transmission, the mean suitability for each calendar month, and the "spillover potential," a measure incorporating suitability with human and livestock populations. RESULTS: Several countries where cases have not yet been reported are suitable for RVF. Areas across the region of interest are suitable for transmission at different times of the year, and some areas are suitable for multiple seasons each year. Spillover potential results show areas within countries where high populations of humans and livestock are at risk for much of the year. CONCLUSIONS: The widespread environmental suitability of RVF highlights the need for increased preparedness, even in countries that have not previously experienced cases. These maps can aid in prioritizing long-term RVF preparedness activities and determining optimal times for recurring preparedness activities. Given an outbreak, our results can highlight areas often at risk for subsequent transmission that month, enabling decision-makers to target responses effectively.

A database of geopositioned Middle East Respiratory Syndrome Coronavirus occurrences.

As a World Health Organization Research and Development Blueprint priority pathogen, there is a need to better understand the geographic distribution of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and its potential to infect mammals and humans. This database documents cases of MERS-CoV globally, with specific attention paid to zoonotic transmission. An initial literature search was conducted in PubMed, Web of Science, and Scopus; after screening articles according to the inclusion/exclusion criteria, a total of 208 sources were selected for extraction and geo-positioning. Each MERS-CoV occurrence was assigned one of the following classifications based upon published contextual information: index, unspecified, secondary, mammal, environmental, or imported. In total, this database is comprised of 861 unique geo-positioned MERS-CoV occurrences. The purpose of this article is to share a collated MERS-CoV database and extraction protocol that can be utilized in future mapping efforts for both MERS-CoV and other infectious diseases. More broadly, it may also provide useful data for the development of targeted MERS-CoV surveillance, which would prove invaluable in preventing future zoonotic spillover.

The current and future global distribution and population at risk of dengue.

Dengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world's population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

A database of geopositioned onchocerciasis prevalence data.

Onchocerciasis is a neglected tropical disease with numerous symptoms and side effects, and when left untreated can lead to permanent blindness or skin disease. This database is an attempt to combine onchocerciasis prevalence data from peer-reviewed publications into a single open-source dataset. The process followed to extract and format the information has been detailed in this paper. A total of 14,043 unique location, diagnostic, age and sex-specific records from 1975-2017 have been collected, organized and marked for collapse where a single geo-position is shared between multiple records. The locations vary from single villages up to smaller administrative units and onchocerciasis control program-defined foci. This resulting database can be used to by the global health community to advance understanding of the distribution of onchocerciasis infection and disease.

Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

This Article was mistakenly not made Open Access when originally published; this has now been amended, and information about the Creative Commons Attribution 4.0 International License has been added into the 'Additional information' section.

Publisher Correction: Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

In the version of this Article originally published, the affiliation for author Catherine Linard was incorrectly stated as '6Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK'. The correct affiliation is '9Spatial Epidemiology Lab (SpELL), Universite Libre de Bruxelles, Brussels, Belgium'. The affiliation for author Hongjie Yu was also incorrectly stated as '11Department of Statistics, Harvard University, Cambridge, MA, USA'. The correct affiliation is '15School of Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China'. This has now been amended in all versions of the Article.

Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus.

The global population at risk from mosquito-borne diseases-including dengue, yellow fever, chikungunya and Zika-is expanding in concert with changes in the distribution of two key vectors: Aedes aegypti and Aedes albopictus. The distribution of these species is largely driven by both human movement and the presence of suitable climate. Using statistical mapping techniques, we show that human movement patterns explain the spread of both species in Europe and the United States following their introduction. We find that the spread of Ae. aegypti is characterized by long distance importations, while Ae. albopictus has expanded more along the fringes of its distribution. We describe these processes and predict the future distributions of both species in response to accelerating urbanization, connectivity and climate change. Global surveillance and control efforts that aim to mitigate the spread of chikungunya, dengue, yellow fever and Zika viruses must consider the so far unabated spread of these mosquitos. Our maps and predictions offer an opportunity to strategically target surveillance and control programmes and thereby augment efforts to reduce arbovirus burden in human populations globally.

Trends and Patterns of Geographic Variation in Mortality From Substance Use Disorders and Intentional Injuries Among US Counties, 1980-2014.

Importance: Substance use disorders, including alcohol use disorders and drug use disorders, and intentional injuries, including self-harm and interpersonal violence, are important causes of early death and disability in the United States. Objective: To estimate age-standardized mortality rates by county from alcohol use disorders, drug use disorders, self-harm, and interpersonal violence in the United States. Design and Setting: Validated small-area estimation models were applied to deidentified death records from the National Center for Health Statistics (NCHS) and population counts from the US Census Bureau, NCHS, and the Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 for alcohol use disorders, drug use disorders, self-harm, and interpersonal violence. Exposures: County of residence. Main Outcomes and Measures: Age-standardized mortality rates by US county (N = 3110), year, sex, and cause. Results: Between 1980 and 2014, there were 2 848 768 deaths due to substance use disorders and intentional injuries recorded in the United States. Mortality rates from alcohol use disorders (n = 256 432), drug use disorders (n = 542 501), self-harm (n = 1 289 086), and interpersonal violence (n = 760 749) varied widely among counties. Mortality rates decreased for alcohol use disorders, self-harm, and interpersonal violence at the national level between 1980 and 2014; however, over the same period, the percentage of counties in which mortality rates increased for these causes was 65.4% for alcohol use disorders, 74.6% for self-harm, and 6.6% for interpersonal violence. Mortality rates from drug use disorders increased nationally and in every county between 1980 and 2014, but the relative increase varied from 8.2% to 8369.7%. Relative and absolute geographic inequalities in mortality, as measured by comparing the 90th and 10th percentile among counties, decreased for alcohol use disorders and interpersonal violence but increased substantially for drug use disorders and self-harm between 1980 and 2014. Conclusions and Relevance: Mortality due to alcohol use disorders, drug use disorders, self-harm, and interpersonal violence varied widely among US counties, both in terms of levels of mortality and trends. These estimates may be useful to inform efforts to target prevention, diagnosis, and treatment to improve health and reduce inequalities.

Trends and Patterns of Differences in Infectious Disease Mortality Among US Counties, 1980-2014.

Importance: Infectious diseases are mostly preventable but still pose a public health threat in the United States, where estimates of infectious diseases mortality are not available at the county level. Objective: To estimate age-standardized mortality rates and trends by county from 1980 to 2014 from lower respiratory infections, diarrheal diseases, HIV/AIDS, meningitis, hepatitis, and tuberculosis. Design and Setting: This study used deidentified death records from the National Center for Health Statistics (NCHS) and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. Validated small-area estimation models were applied to these data to estimate county-level infectious disease mortality rates. Exposures: County of residence. Main Outcomes and Measures: Age-standardized mortality rates of lower respiratory infections, diarrheal diseases, HIV/AIDS, meningitis, hepatitis, and tuberculosis by county, year, and sex. Results: Between 1980 and 2014, there were 4 081 546 deaths due to infectious diseases recorded in the United States. In 2014, a total of 113 650 (95% uncertainty interval [UI], 108 764-117 942) deaths or a rate of 34.10 (95% UI, 32.63-35.38) deaths per 100 000 persons were due to infectious diseases in the United States compared to a total of 72 220 (95% UI, 69 887-74 712) deaths or a rate of 41.95 (95% UI, 40.52-43.42) deaths per 100 000 persons in 1980, an overall decrease of 18.73% (95% UI, 14.95%-23.33%). Lower respiratory infections were the leading cause of infectious diseases mortality in 2014 accounting for 26.87 (95% UI, 25.79-28.05) deaths per 100 000 persons (78.80% of total infectious diseases deaths). There were substantial differences among counties in death rates from all infectious diseases. Lower respiratory infection had the largest absolute mortality inequality among counties (difference between the 10th and 90th percentile of the distribution, 24.5 deaths per 100 000 persons). However, HIV/AIDS had the highest relative mortality inequality between counties (10.0 as the ratio of mortality rate in the 90th and 10th percentile of the distribution). Mortality from meningitis and tuberculosis decreased over the study period in all US counties. However, diarrheal diseases were the only cause of infectious diseases mortality to increase from 2000 to 2014, reaching a rate of 2.41 (95% UI, 0.86-2.67) deaths per 100 000 persons, with many counties of high mortality extending from Missouri to the northeastern region of the United States. Conclusions and Relevance: Between 1980 and 2014, there were declines in mortality from most categories of infectious diseases, with large differences among US counties. However, over this time there was an increase in mortality for diarrheal diseases.

Variation in life expectancy and mortality by cause among neighbourhoods in King County, WA, USA, 1990-2014: a census tract-level analysis for the Global Burden of Disease Study 2015.

BACKGROUND: Health outcomes are known to vary at both the country and local levels, but trends in mortality across a detailed and comprehensive set of causes have not been previously described at a very local level. Life expectancy in King County, WA, USA, is in the 95th percentile among all counties in the USA. However, little is known about how life expectancy and mortality from different causes of death vary at a local, neighbourhood level within this county. In this analysis, we estimated life expectancy and cause-specific mortality within King County to describe spatial trends, quantify disparities in mortality, and assess the contribution of each cause of death to overall disparities in all-cause mortality. METHODS: We applied established so-called garbage code redistribution algorithms and small area estimation methods to death registration data for King County to estimate life expectancy, cause-specific mortality rates, and years of life lost (YLL) rates from 152 causes of death for 397 census tracts from Jan 1, 1990, to Dec 31, 2014. We used the cause list developed for the Global Burden of Disease 2015 study for this analysis. Deaths were tabulated by age group, sex, census tract, and cause of death. We used Bayesian mixed-effects regression models to estimate mortality overall and from each cause. FINDINGS: Between 1990 and 2014, life expectancy in King County increased by 5·4 years (95% uncertainty interval [UI] 5·0-5·7) among men (from 74·0 years [73·7-74·3] to 79·3 years [79·1-79·6]) and by 3·4 years (3·0-3·7) among women (from 80·0 years [79·7-80·2] to 83·3 years [83·1-83·5]). In 2014, life expectancy ranged from 68·4 years (95% UI 66·9-70·1) to 86·7 years (85·0-88·2) for men and from 73·6 years (71·6-75·5) to 88·4 years (86·9-89·9) for women among census tracts within King County. Rates of YLL by cause also varied substantially among census tracts for each cause of death. Geographical areas with relatively high and relatively low YLL rates differed by cause. In general, causes of death responsible for more YLLs overall also contributed more significantly to geographical inequality within King County. However, certain causes contributed more to inequality than to overall YLLs. INTERPRETATION: This census tract-level analysis of life expectancy and cause-specific YLL rates highlights important differences in health among neighbourhoods in King County that are masked by county-level estimates. Efforts to improve population health in King County should focus on reducing geographical inequality, by targeting those health conditions that contribute the most to overall YLLs and to inequality. This analysis should be replicated in other locations to more fully describe fine-grained local-level variation in population health and contribute to efforts to improve health while reducing inequalities. FUNDING: John W Stanton and Theresa E Gillespie.

Trends and Patterns of Differences in Chronic Respiratory Disease Mortality Among US Counties, 1980-2014.

Importance: Chronic respiratory diseases are an important cause of death and disability in the United States. Objective: To estimate age-standardized mortality rates by county from chronic respiratory diseases. Design, Setting, and Participants: Validated small area estimation models were applied to deidentified death records from the National Center for Health Statistics and population counts from the US Census Bureau, National Center for Health Statistics, and Human Mortality Database to estimate county-level mortality rates from 1980 to 2014 for chronic respiratory diseases. Exposure: County of residence. Main Outcomes and Measures: Age-standardized mortality rates by county, year, sex, and cause. Results: A total of 4 616 711 deaths due to chronic respiratory diseases were recorded in the United States from January 1, 1980, through December 31, 2014. Nationally, the mortality rate from chronic respiratory diseases increased from 40.8 (95% uncertainty interval [UI], 39.8-41.8) deaths per 100 000 population in 1980 to a peak of 55.4 (95% UI, 54.1-56.5) deaths per 100 000 population in 2002 and then declined to 52.9 (95% UI, 51.6-54.4) deaths per 100 000 population in 2014. This overall 29.7% (95% UI, 25.5%-33.8%) increase in chronic respiratory disease mortality from 1980 to 2014 reflected increases in the mortality rate from chronic obstructive pulmonary disease (by 30.8% [95% UI, 25.2%-39.0%], from 34.5 [95% UI, 33.0-35.5] to 45.1 [95% UI, 43.7-46.9] deaths per 100 000 population), interstitial lung disease and pulmonary sarcoidosis (by 100.5% [95% UI, 5.8%-155.2%], from 2.7 [95% UI, 2.3-4.2] to 5.5 [95% UI, 3.5-6.1] deaths per 100 000 population), and all other chronic respiratory diseases (by 42.3% [95% UI, 32.4%-63.8%], from 0.51 [95% UI, 0.48-0.54] to 0.73 [95% UI, 0.69-0.78] deaths per 100 000 population). There were substantial differences in mortality rates and changes in mortality rates over time among counties, and geographic patterns differed by cause. Counties with the highest mortality rates were found primarily in central Appalachia for chronic obstructive pulmonary disease and pneumoconiosis; widely dispersed throughout the Southwest, northern Great Plains, New England, and South Atlantic for interstitial lung disease; along the southern half of the Mississippi River and in Georgia and South Carolina for asthma; and in southern states from Mississippi to South Carolina for other chronic respiratory diseases. Conclusions and Relevance: Despite recent declines in mortality from chronic respiratory diseases, mortality rates in 2014 remained significantly higher than in 1980. Between 1980 and 2014, there were important differences in mortality rates and changes in mortality by county, sex, and particular chronic respiratory disease type. These estimates may be helpful for informing efforts to improve prevention, diagnosis, and treatment.