Ebola Virus Disease Outbreaks: Lessons Learned From Past and Facing Future Challenges.

INTRODUCTION: The purpose of this review is to examine African Ebola outbreaks from their first discovery to the present, to determine how the medical and public health response has changed and identify the causes for those changes. We sought to describe what is now known about the epidemiology and spread of Ebola virus disease (EVD) from the significant outbreaks that have occurred and outbreak control methods applied under often challenging circumstances. Given the substantial role that the U.S. Government and the U.S. DoD have played in the 2014 to 2016 West African Ebola outbreak, the role of the DoD and the U.S. Africa Command in controlling EVD is described. MATERIALS AND METHODS: A descriptive method design was used to collect and analyze all available Ebola outbreak literature using the PubMed database. An initial literature search was conducted by searching for, obtaining, and reading original source articles on all major global Ebola outbreaks. To conduct a focused search, we used initial search terms "Ebola outbreak," "Ebola virus disease," "Ebola response," "Ebola countermeasures," and also included each country's name where Ebola cases are known to have occurred. From the 4,673 unique articles obtained from this search and subsequent article title review, 307 articles were identified for potential inclusion. Following abstract and article review, 45 original source articles were used to compile the history of significant Ebola outbreaks. From this compilation, articles focused on each respective subsection of this review to delineate and describe the history of EVD and response, identifying fundamental changes, were obtained and incorporated. RESULTS: We present known Ebola virus and disease attributes, including a general description, seasonality and location, transmission capacity, clinical symptoms, surveillance, virology, historical EVD outbreaks and response, international support for Ebola outbreak response, U.S. DoD support, medical countermeasures supporting outbreak response, remaining gaps to include policy limitations, regional instability, climate change, migration, and urbanization, public health education and infrastructure, and virus persistence and public awareness. CONCLUSIONS: The health and societal impacts of EVD on Africa has been far-reaching, with about 35,000 cases and over 15,000 deaths, with small numbers of cases spreading globally. However, the history of combatting EVD reveals that there is considerable hope for African nations to quickly and successfully respond to Ebola outbreaks, through use of endemic resources including Africa CDC and African Partner Outbreak Response Alliance and the U.S. Africa Command with greater DoD reachback. Although there remains much to be learned about the Ebola virus and EVD including whether the potential for novel strains to become deadly emerging infections, invaluable vaccines, antivirals, and public health measures are now part of the resources that can be used to combat this disease.

Drinking water and health assessment in a Northern Arizona community.

Arizona is a mineral rich state that relies on a mix of surface and ground water supplies for drinking water requirements. Small, rural water systems relying on groundwater frequently encounter elevated metal(loid) measures, particularly inorganic arsenic (As +3, +5). Such contaminant occurrences can be associated with adverse health outcomes including cancers. The Hopi Environmental Health Project examined drinking water quality and water consumption behaviors from 76 homes on Hopi lands over a four-year period. Water samples were analyzed for 28 elements and compared to US Environmental Protection Agengy (EPA) maximum contaminant levels (MCL). Only municipal/piped water had a mean arsenic concentration (11.01 µg/L) exceeding the MCL (10.0 µg/L). All other water types and elements occurred below MCL when detected. A lifetime cancer and hazard quotient associated with arsenic consumption through each water type was performed and piped/municipal water was found to carry the greatest risks (9.96 cases per 10,000 people). Results from this study showed the potential for multiple contaminants to be present in drinking water from Hopi lands and the need for further health assessment of routine exposure to low doses of contaminant mixtures through drinking water.

Notional Spread of Cholera in Haiti Following a Natural Disaster: Considerations for Military and Disaster Relief Personnel.

INTRODUCTION: Cholera remains a significant public health threat for many countries, and the severity largely varies by the population and local conditions that drive disease spread, especially in endemic areas prone to natural disasters and flooding. Epidemiological models can provide useful information to military planners for understanding disease spread within populations and the effectiveness of response options for preventing the transmission among deployed and stationed personnel. This study demonstrates the use of epidemiological modeling to understand the dynamics of cholera transmission to inform emergency planning and military preparedness in areas with highly communicable diseases. MATERIALS AND METHODS: Areas with higher probability for a potential cholera outbreak in Haiti followed by a natural disaster were identified. The hotspots were then used to seed an extended compartmental model, EpiGrid, to simulate notional spread scenarios of cholera originating in three distinct areas in Haiti. Disease parameters were derived from the 2010 cholera outbreak in Haiti, and disease spread was simulated over a 12-week period under uncontrolled and controlled spread. RESULTS: For each model location, scenarios of mitigated (intervention with 30% transmission reduction via international aid) and unmitigated (without intervention) are simulated. The results depict the geographical spread and estimate the cumulative cholera infection for each notional scenario over the course of 3 months. Disease transmission differs considerably across origin site with an outbreak originating in the department of Nippes spanning the largest geographic area and resulting in the largest number of cumulative cases after 12 weeks under unmitigated (79,518 cases) and mitigated (35,667 cases) spread scenarios. CONCLUSIONS: We modeled the notional re-emergence and spread of cholera following the August 2021 earthquake in Haiti while in the midst of the global COVID-19 pandemic. This information can help guide military and emergency response decision-making during an infectious disease outbreak and considerations for protecting military personnel in the midst of a humanitarian response. Military planners should consider the use of epidemiological models to assess the health risk posed to deployed and stationed personnel in high-risk areas.

A Universal Travel Risk Assessment Questionnaire: Travel Assessment During COVID-19 Pandemic and Endemicity.

INTRODUCTION: Throughout the Coronavirus Disease 2019 (COVID-19) pandemic, military commanders have been challenged with providing appropriate travel guidance for their military and civilian personnel and dependents. This guidance, where promulgated, lacks uniformity. Travel aids and computer applications similarly differ and are not updated as often as jurisdictional travel health guidance is changed. Given the ever-evolving Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants with differing degrees of infectivity, COVID-19 travel guidance will remain relevant for military travelers during the transition from pandemic to endemic phases and for the foreseeable future. MATERIALS AND METHODS: We reviewed all germane travel guidance promulgated by the U.S, Department of Defense; the U.S. Centers for Disease Control and Prevention; and other federal, state, and international agencies. From these materials, we identified and delineated applicable universal components for COVID-19 travel risk and created a universal Travel Risk Assessment Questionnaire (TRAQ). RESULTS: We present a universal TRAQ that identifies and allows for a graded most-appropriate response to known travel risk assessment factors including travel restrictions, travel mode, travel time, travel party size, trip duration, COVID-19 incidence rate at travel destination, lodging, planned activities, personal interaction level, vaccination coverage at destination, travel location, traveler's vaccination status, previous COVID-19 infection, mask wear compliance, mask type, and work environment, along with additional considerations and post-travel COVID-19 questions. We provide examples of the use of this questionnaire that describe low, medium, and high risk to the traveler for contracting COVID-19. CONCLUSION: Our TRAQ provides an easy-to-use format that can enable military, business, or personal travelers to more completely assess their likelihood of COVID-19 exposure and help them to reduce their potential for contracting COVID-19 during travel and subsequently transmitting it to others upon return. It should help commanders and traveling personnel to better assess COVID-19 travel risks through application of known travel risk factors.

Coronavirus Disease 2019 on the Heels of Ebola Virus Disease in West Africa.

This study utilized modeling and simulation to examine the effectiveness of current and potential future COVID-19 response interventions in the West African countries of Guinea, Liberia, and Sierra Leone. A comparison between simulations can highlight which interventions could have an effect on the pandemic in these countries. An extended compartmental model was used to run simulations incorporating multiple vaccination strategies and non-pharmaceutical interventions (NPIs). In addition to the customary categories of susceptible, exposed, infected, and recovered (SEIR) compartments, this COVID-19 model incorporated early and late disease states, isolation, treatment, and death. Lessons learned from the 2014-2016 Ebola virus disease outbreak-especially the optimization of each country's resource allocation-were incorporated in the presented models. For each country, models were calibrated to an estimated number of infections based on actual reported cases and deaths. Simulations were run to test the potential future effects of vaccination and NPIs. Multiple levels of vaccination were considered, based on announced vaccine allocation plans and notional scenarios. Increased vaccination combined with NPI mitigation strategies resulted in thousands of fewer COVID-19 infections in each country. This study demonstrates the importance of increased vaccinations. The levels of vaccination in this study would require substantial increases in vaccination supplies obtained through national purchases or international aid. While this study does not aim to develop a model that predicts the future, it can provide useful information for decision-makers in low- and middle-income nations. Such information can be used to prioritize and optimize limited available resources for targeted interventions that will have the greatest impact on COVID-19 pandemic response.

Operational Considerations in Global Health Modeling.

Epidemiological modeling and simulation can contribute cooperatively across multifaceted areas of biosurveillance systems. These efforts can be used to support real-time decision-making during public health emergencies and response operations. Robust epidemiological modeling and simulation tools are crucial to informing risk assessment, risk management, and other biosurveillance processes. The Defense Threat Reduction Agency (DTRA) has sponsored the development of numerous modeling and decision support tools to address questions of operational relevance in response to emerging epidemics and pandemics. These tools were used during the ongoing COVID-19 pandemic and the Ebola outbreaks in West Africa and the Democratic Republic of the Congo. This perspective discusses examples of the considerations DTRA has made when employing epidemiological modeling to inform on public health crises and highlights some of the key lessons learned. Future considerations for researchers developing epidemiological modeling tools to support biosurveillance and public health operations are recommended.

Household and behavioral determinants of indoor PM2.5 in a rural solid fuel burning Native American community.

Indoor and outdoor concentrations of PM2.5 were measured for 24 h during heating and non-heating seasons in a rural solid fuel burning Native American community. Household building characteristics were collected during the initial home sampling visit using technician walkthrough questionnaires, and behavioral factors were collected through questionnaires by interviewers. To identify seasonal behavioral factors and household characteristics associated with indoor PM2.5 , data were analyzed separately by heating and non-heating seasons using multivariable regression. Concentrations of PM2.5 were significantly higher during the heating season (indoor: 36.2 µg/m3 ; outdoor: 22.1 µg/m3 ) compared with the non-heating season (indoor: 14.6 µg/m3 ; outdoor: 9.3 µg/m3 ). Heating season indoor PM2.5 was strongly associated with heating fuel type, housing type, indoor pests, use of a climate control unit, number of interior doors, and indoor relative humidity. During the non-heating season, different behavioral and household characteristics were associated with indoor PM2.5 concentrations (indoor smoking and/or burning incense, opening doors and windows, area of surrounding environment, building size and height, and outdoor PM2.5 ). Homes heated with coal and/or wood, or a combination of coal and/or wood with electricity and/or natural gas had elevated indoor PM2.5 concentrations that exceeded both the EPA ambient standard (35 µg/m3 ) and the WHO guideline (25 µg/m3 ).

Imputation methods for addressing missing data in short-term monitoring of air pollutants.

Monitoring of environmental contaminants is a critical part of exposure sciences research and public health practice. Missing data are often encountered when performing short-term monitoring (<24 h) of air pollutants with real-time monitors, especially in resource-limited areas. Approaches for handling consecutive periods of missing and incomplete data in this context remain unclear. Our aim is to evaluate existing imputation methods for handling missing data for real-time monitors operating for short durations. In a current field-study, realtime PM2.5 monitors were placed outside of 20 households and ran for 24-hours. Missing data was simulated in these households at four consecutive periods of missingness (20%, 40%, 60%, 80%). Univariate (Mean, Median, Last Observation Carried Forward, Kalman Filter, Random, Markov) and multivariate time-series (Predictive Mean Matching, Row Mean Method) methods were used to impute missing concentrations, and performance was evaluated using five error metrics (Absolute Bias, Percent Absolute Error in Means, R2 Coefficient of Determination, Root Mean Square Error, Mean Absolute Error). Univariate methods of Markov, random, and mean imputations were the best performing methods that yielded 24-hour mean concentrations with the lowest error and highest R2 values across all levels of missingness. When evaluating error metrics minute-by-minute, Kalman filters, median, and Markov methods performed well at low levels of missingness (20-40%). However, at higher levels of missingness (60-80%), Markov, random, median, and mean imputation performed best on average. Multivariate methods were the worst performing imputation methods across all levels of missingness. Imputation using univariate methods may provide a reasonable solution to addressing missing data for short-term monitoring of air pollutants, especially in resource-limited areas. Further efforts are needed to evaluate imputation methods that are generalizable across a diverse range of study environments.

Obesity and trauma mortality: Sizing up the risks in motor vehicle crashes.

BACKGROUND: Protective effects of safety devices in obese motorists in motor vehicle collisions (MVC) remain unclear. Aim of our study is to assess the association between morbid obesity and mortality in MVC, and to determine the efficacy of protective devices. We hypothesised that patients with morbid obesity will be at greater risk of death after MVC. METHODS: A retrospective analysis of MVC patients (age ≥16 y.o.) was performed using the National Trauma Data Bank from 2007 to 2010. Patients with recorded comorbidity of morbid obesity (BMI≥40) were identified. Patients dead on arrival, with isolated traumatic brain injury, or incomplete data were excluded. The primary outcome was in-hospital mortality. Multivariate logistic regression was performed. RESULTS: Our sample of 214,306 MVC occupants included 10,260 (4.8%) morbidly obese patients. Mortality risk was greatest among occupants with morbid obesity (ORcrude 1.74 [1.54-1.98]). After adjusting for patient demographics, safety device and physiological severity, odds of death was 1.52 [1.33-1.74] times greater in motorists with morbid obesity. Motorists with morbid obesity were at greater risk of death if no restraint (OR 1.84 [1.47-2.31]), seatbelt only (OR 1.48 [1.17-1.86]), or both seatbelt and airbag were present (OR 1.49 [1.13-1.97]). No significant differences in the odds of death exist between drivers with morbid obesity and non-morbidly obese drivers with only airbag deployment (OR 0.99 [0.65-1.51]). CONCLUSIONS: Motorists with morbid obesity are at greater risk of MVC. Regardless of safety device use, occupants with morbid obesity remained at greater risk of death. Further research examining the effectiveness of vehicle restraints in drivers with morbid obesity is warranted.

Morbid obesity predisposes trauma patients to worse outcomes: a National Trauma Data Bank analysis.

BACKGROUND: One third of US adults are obese. The impact of obesity on outcomes after blunt traumatic injury has been studied with discrepant results. The aim of our study was to evaluate outcomes in morbidly obese patients after blunt trauma. We hypothesized that morbidly obese patients have adverse outcomes as compared with nonobese patients after blunt traumatic injury. METHODS: We performed a retrospective analysis of all blunt trauma patients (≥18 years) using the National Trauma Data Bank for years 2007 to 2010. Patients with recorded comorbidity of morbid obesity (body mass index ≥ 40) were identified. Patients transferred, dead on arrival, and with isolated traumatic brain injury were excluded. Propensity score matching was used to match morbidly obese patients to non-morbidly obese patients (body mass index < 40) in a 1:1 ratio based on age, sex, Injury Severity Score (ISS), Glasgow Coma Scale (GCS), and systolic blood pressure on presentation. The primary outcome was mortality, and the secondary outcome was hospital complications. RESULTS: A total of 32,780 patients (morbidly obese, 16,390; nonobese, 16,390) were included in the study. Morbidly obese patients were more likely to have in-hospital complications (odds ratio [OR], 1.8, 95% confidence interval [CI], 1.6-1.9), longer hospital stay (OR, 1.2; 95% CI, 1.1-1.3), and longer intensive care unit stay (OR, 1.15; 95% CI, 1.09-1.2). The overall mortality rate was 2.8% (n = 851). Mortality was higher in morbidly obese patients compared with the nonobese patients (3.0 vs. 2.2; OR, 1.4; 95% CI, 1.1-1.5). CONCLUSION: In a cohort of matched patients, morbid obesity is a risk factor for the development of in-hospital complications and mortality after blunt traumatic injury. The results of our study call for attention through focused injury prevention efforts. Future studies are needed to help define the consequences of obesity that influence outcomes. LEVEL OF EVIDENCE: Prognostic study, level III.