Assessing the relationship between epidemic growth scaling and epidemic size: The 2014-16 Ebola epidemic in West Africa.

We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014-16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising at least 7 weeks of epidemic growth. We then study how these parameters are associated with observed epidemic sizes. For validation purposes, we also analyse two historic Ebola outbreaks. We find a high monotonic association between the scaling of epidemic growth parameter and the observed epidemic size. For example, scaling of growth parameters around 0.3-0.4, 0.4-0.6 and 0.6 are associated with epidemic sizes on the order of 350-460, 460-840 and 840-2500 cases, respectively. These results are not explained by differences in epidemic onset across affected areas. We also find the relationship between the scaling of epidemic growth parameter and the observed epidemic size to be consistent for two past Ebola outbreaks in Congo (1976) and Uganda (2000). Signature features of epidemic growth could become useful to assess the risk of observing a major epidemic outbreak, generate improved diseases forecasts and enhance the predictive power of epidemic models. Our results indicate that the epidemic growth scaling parameter is a useful indicator of epidemic size, which may have significant implications to guide control of Ebola outbreaks and possibly other infectious diseases.

Six-monthly appointment spacing for clinical visits as a model for retention in HIV Care in Conakry-Guinea: a cohort study.

BACKGROUND: The outbreak of the Ebola virus disease (EVD) in 2014 led to massive dropouts in HIV care in Guinea. Meanwhile, Médecins Sans Frontières (MSF) was implementing a six-monthly appointment spacing approach adapted locally as Rendez-vous de Six Mois (R6M) with an objective to improve retention in care. We sought to evaluate this innovative model of ART delivery in circumstances where access to healthcare is restricted. METHODS: A retrospective cohort study in 2014 of the outcome of a group of stable patients (viral load ≤1000 copies/µl) enrolled voluntarily in R6M compared with a group of stable patients continuing standard one to three monthly visits in Conakry. Log-rank test and Cox proportional hazards model were used to compare rates of attrition (deaths and defaulters) from care between the two groups. A linear regression analysis was used to describe the trend or pattern in the number of clinical visits over time. RESULTS: Included were 1957 adults of 15 years old and above of whom 1166 (59.6%) were enrolled in the R6M group and 791 (40.4%) in the standard care group. The proportion remaining in care at 18 months and beyond was 90% in the R6M group; significantly higher than the 75% observed in the control group (p < 0.0001). After adjusting for duration on ART and tuberculosis co-infection as covariates, the R6M strategy was associated with a 60% reduction in the rate of attrition from care compared with standard care (adjusted Hazard Ratio = 0.40, 95%CI: 0.27-0.59, p < 0.001). There was a negative secular trend in the number of monthly clinical visits for 24 months as the predicted caseload reduced on average by just below 50 visits per month (ß = -48.6, R2 = 0.82, p < 0.0001). CONCLUSION: R6M was likely to reduce staff workload and to mitigate attrition from ART care for stable patients in Conakry despite restricted access to healthcare caused by the devastating EVD on the health system in Guinea. R6M could be rolled out as the model of care for stable patients where and when feasible as a strategy likely to improve retention in HIV care.

The Ebola epidemic in West Africa: challenges, opportunities, and policy priority areas.

The ongoing Ebola epidemic in West Africa has drawn attention to global health inequalities, in particular the inadequacies of health care systems in sub-Saharan African countries for appropriately managing and containing infectious diseases. The purpose of this article is to examine the sociopolitical and economic conditions that created the environment for the Ebola epidemic to occur, identify challenges to and opportunities for the prevention and control of Ebola and future outbreaks, and discuss policy recommendations and priority areas for addressing the Ebola epidemic and future outbreaks in West Africa. Articles in peer-reviewed journals on health system reforms in developing countries and periodicals of international organizations were used to gather the overview reported in this article. We identify individual, structural, and community challenges that must be addressed in an effort to reduce the spread of Ebola in West Africa. The Ebola epidemic in West Africa underscores the need for the overhaul and transformation of African health care systems to build the capacity in these countries to address infectious diseases. Public-private partnerships for investment in developing countries' health care systems that involve the international community are critical in addressing the current Ebola epidemic and future outbreaks.

The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt.

Infectious disease forecasting is gaining traction in the public health community; however, limited systematic comparisons of model performance exist. Here we present the results of a synthetic forecasting challenge inspired by the West African Ebola crisis in 2014-2015 and involving 16 international academic teams and US government agencies, and compare the predictive performance of 8 independent modeling approaches. Challenge participants were invited to predict 140 epidemiological targets across 5 different time points of 4 synthetic Ebola outbreaks, each involving different levels of interventions and "fog of war" in outbreak data made available for predictions. Prediction targets included 1-4 week-ahead case incidences, outbreak size, peak timing, and several natural history parameters. With respect to weekly case incidence targets, ensemble predictions based on a Bayesian average of the 8 participating models outperformed any individual model and did substantially better than a null auto-regressive model. There was no relationship between model complexity and prediction accuracy; however, the top performing models for short-term weekly incidence were reactive models with few parameters, fitted to a short and recent part of the outbreak. Individual model outputs and ensemble predictions improved with data accuracy and availability; by the second time point, just before the peak of the epidemic, estimates of final size were within 20% of the target. The 4th challenge scenario - mirroring an uncontrolled Ebola outbreak with substantial data reporting noise - was poorly predicted by all modeling teams. Overall, this synthetic forecasting challenge provided a deep understanding of model performance under controlled data and epidemiological conditions. We recommend such "peace time" forecasting challenges as key elements to improve coordination and inspire collaboration between modeling groups ahead of the next pandemic threat, and to assess model forecasting accuracy for a variety of known and hypothetical pathogens.

The large graph limit of a stochastic epidemic model on a dynamic multilayer network.

We consider a Markovian SIR-type (Susceptible → Infected → Recovered) stochastic epidemic process with multiple modes of transmission on a contact network. The network is given by a random graph following a multilayer configuration model where edges in different layers correspond to potentially infectious contacts of different types. We assume that the graph structure evolves in response to the epidemic via activation or deactivation of edges of infectious nodes. We derive a large graph limit theorem that gives a system of ordinary differential equations (ODEs) describing the evolution of quantities of interest, such as the proportions of infected and susceptible vertices, as the number of nodes tends to infinity. Analysis of the limiting system elucidates how the coupling of edge activation and deactivation to infection status affects disease dynamics, as illustrated by a two-layer network example with edge types corresponding to community and healthcare contacts. Our theorem extends some earlier results describing the deterministic limit of stochastic SIR processes on static, single-layer configuration model graphs. We also describe precisely the conditions for equivalence between our limiting ODEs and the systems obtained via pair approximation, which are widely used in the epidemiological and ecological literature to approximate disease dynamics on networks. The flexible modeling framework and asymptotic results have potential application to many disease settings including Ebola dynamics in West Africa, which was the original motivation for this study.

Key data for outbreak evaluation: building on the Ebola experience.

Following the detection of an infectious disease outbreak, rapid epidemiological assessment is critical for guiding an effective public health response. To understand the transmission dynamics and potential impact of an outbreak, several types of data are necessary. Here we build on experience gained in the West African Ebola epidemic and prior emerging infectious disease outbreaks to set out a checklist of data needed to: (1) quantify severity and transmissibility; (2) characterize heterogeneities in transmission and their determinants; and (3) assess the effectiveness of different interventions. We differentiate data needs into individual-level data (e.g. a detailed list of reported cases), exposure data (e.g. identifying where/how cases may have been infected) and population-level data (e.g. size/demographics of the population(s) affected and when/where interventions were implemented). A remarkable amount of individual-level and exposure data was collected during the West African Ebola epidemic, which allowed the assessment of (1) and (2). However, gaps in population-level data (particularly around which interventions were applied when and where) posed challenges to the assessment of (3). Here we highlight recurrent data issues, give practical suggestions for addressing these issues and discuss priorities for improvements in data collection in future outbreaks.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

A Review of Pediatric Critical Care in Resource-Limited Settings: A Look at Past, Present, and Future Directions.

Fifteen years ago, United Nations world leaders defined millenium development goal 4 (MDG 4): to reduce under-5-year mortality rates by two-thirds by the year 2015. Unfortunately, only 27 of 138 developing countries are expected to achieve MDG 4. The majority of childhood deaths in these settings result from reversible causes, and developing effective pediatric emergency and critical care services could substantially reduce this mortality. The Ebola outbreak highlighted the fragility of health care systems in resource-limited settings and emphasized the urgent need for a paradigm shift in the global approach to healthcare delivery related to critical illness. This review provides an overview of pediatric critical care in resource-limited settings and outlines strategies to address challenges specific to these areas. Implementation of these tools has the potential to move us toward delivery of an adequate standard of critical care for all children globally, and ultimately decrease global child mortality in resource-limited settings.

Controlling Ebola: what we can learn from China's 1911 battle against the pneumonic plague in Manchuria.

The pneumonic plague, which spread across Northeast China during the winter of 1910 and spring of 1911, caused numerous deaths and brought about severe social turmoil. After compulsory quarantine and other epidemic prevention measures were enforced by Dr Wu Lien-teh, the epidemic was brought to an end within 4 months. This article reviews the ways in which the plague was dealt with from a historical perspective, based on factors such as clinical manifestations, duration of illness, case fatality rate, degree of transmissibility, poverty, inadequate healthcare infrastructure, and the region's recent strife-filled history. Similarities were sought between the pneumonic plague in Northeast China in the twentieth century and the Ebola virus outbreak that is currently ravaging Africa, and an effort made to summarize the ways in which specific measures were applied successfully to fight the earlier epidemic. Our efforts highlight valuable experiences that are of potential benefit in helping to fight the current rampant Ebola epidemic in West Africa.

What does the public know about Ebola? The public's risk perceptions regarding the current Ebola outbreak in an as-yet unaffected country.

BACKGROUND: The unexpected developments surrounding the Ebola virus in the United States provide yet another warning that we need to establish communication preparedness. This study examines what the Israeli public knew about Ebola after the initial stages of the outbreak in a country to which Ebola has not spread and assesses the association between knowledge versus worries and concerns about contracting Ebola. METHODS: Online survey using Google Docs (Google, Mountain View, CA) of Israeli health care professionals and the general public (N = 327). RESULTS: The Israeli public has knowledge about Ebola (mean ± SD, 4.18 ± 0.83), despite the fact that the disease has not spread to Israel. No statistically significant difference was found between health care workers versus non-health care workers in the knowledge score. Additionally, no statistically significant association was found between knowledge and worry levels. The survey indicated that Israelis expect information about Ebola from the health ministry, including topics of uncertainty. More than half of the participants thought the information provided by the health ministry on Ebola and Ebola prevention was insufficient (50.5% and 56.4%, respectively), and almost half (45.2% and 41.1%, respectively) were unsure if the information was sufficient. CONCLUSION: The greatest challenges that the organizations face is not only to convey knowledge, but also to find ways to convey comprehensive information that reflects uncertainty and empowers the public to make fact-based decisions about health.