Modeling the effect of comprehensive interventions on Ebola virus transmission

A novel indicator in epidemic monitoring through a case study of Ebola in West Africa (2014-2016)

The E/S (exposed/susceptible) ratio is analyzed in the SEIR model. The ratio plays a key role in understanding epidemic dynamics during the 2014-2016 Ebola outbreak in Sierra Leone and Guinea. The maximum value of the ratio occurs immediately before or after the time-dependent reproduction number (Rt) equals 1, depending on the initial susceptible population (S(0)). It is demonstrated that transmission rate curves corresponding to various incubation periods intersect at a single point referred to as the Cross Point (CP). At this point, the E/S ratio reaches an extremum, signifying a critical shift in transmission dynamics and aligning with the time when Rt approaches 1. By plotting transmission rate curves, β(t), for any two arbitrary incubation periods and tracking their intersections, we can trace CP over time. CP serves as an indicator of epidemic status, especially when Rt is close to 1. It provides a practical means of monitoring epidemics without prior knowledge of the incubation period. Through a case study, we estimate the transmission rate and reproduction number, identifying CP and Rt = 1 while examining the E/S ratio across various values of S(0).

The basic reproduction number (R0) of ebola virus disease: A systematic review and meta-analysis

BACKGROUND

Ebola virus disease (Ebola) is highly pathogenic, transmissible, and often deadly, with debilitating consequences. Superspreading within a cluster is also possible. In this study, we aim to document Ebola basic reproduction number (R0): the average number of new cases associated with an Ebola case in a completely susceptible population.

METHODS

We undertook a systematic review and meta-analysis. We searched PubMed, EMBASE, and Web of Science for studies published between 1976 and February 27, 2023. We also manually searched the reference lists of the reviewed studies to identify additional studies. We included studies that reported R0 during Ebola outbreaks in Africa. We excluded studies that reported only the effective reproduction number (Rt). Abstracting data from included studies was performed using a pilot-tested standard form. Two investigators reviewed the studies, extracted the data, and assessed quality. The pooled R0 was determined by a random-effects meta-analysis. R0 was stratified by country. We also estimated the theoretically required immunization coverage to reach herd-immunity using the formula of (1-1/R0) × 100 %.

RESULTS

The search yielded 2042 studies. We included 53 studies from six African countries in the systematic review providing 97 Ebola mean R0 estimates. 27 (with 46 data points) studies were included in the meta-analysis. The overall pooled mean Ebola R0 was 1.95 (95 % CI 1.74-2.15), with high heterogeneity (I2 = 99.99 %; τ2 = 0.38; and p < 0.001) and evidence of small-study effects (Egger's statistics: Z = 4.67; p < 0.001). Mean Ebola R0 values ranged from 1.2 to 10.0 in Nigeria, 1.1 to 7 in Guinea, 1.14 to 8.33 in Sierra Leone, 1.13 to 5 in Liberia, 1.2 to 5.2 in DR Congo, 1.34 to 2.7 in Uganda, and from 1.40 to 2.55 for all West African countries combined. Pooled mean Ebola R0 was 9.38 (95 % CI 4.16-14.59) in Nigeria, 3.31 (95 % CI 2.30-4.32) in DR Congo, 2.0 (95 % CI 1.25-2.76) in Uganda, 1.83 (95 % CI 1.61-2.05) in Liberia, 1.73 (95 % CI 1.47-2.0) in Sierra Leonne, and 1.44 (95 % CI 1.29-1.60) in Guinea. In theory, 50 % of the population needs to be vaccinated to achieve herd immunity, assuming that Ebola vaccine would be 100 % effective.

CONCLUSIONS

Ebola R0 varies widely across countries. Ebola has a much wider R0 range than is often claimed (1.3-2.0). It is possible for an Ebola index case to infect more than two susceptible individuals.

Metabolomics Approaches for the Diagnosis, Treatment, and Better Disease Management of Viral Infections

Metabolomics is an analytical approach that involves profiling and comparing the metabolites present in biological samples. This scoping review article offers an overview of current metabolomics approaches and their utilization in evaluating metabolic changes in biological fluids that occur in response to viral infections. Here, we provide an overview of metabolomics methods including high-throughput analytical chemistry and multivariate data analysis to identify the specific metabolites associated with viral infections. This review also focuses on data interpretation and applications designed to improve our understanding of the pathogenesis of these viral diseases.

Stability Analysis Method for Initial Support Structure of Tunnel in Swelling Loess

The stability of tunnel is greatly affected by the changes in volume and strength of swelling loess caused by humidification. Quantitative reflection of the influence of humidification on stability in mechanical model has important engineering significance for the design of support structures. Based on the fact that parameters related to swelling and strength are functions of water content, the water content was introduced into the classical surrounding rock–support model, and a safety factor was employed for the index of stability. Thus, a stability analysis framework of swelling loess tunnel was established by considering the swelling and softening of swelling loess. In an engineering case, the theoretical models in this paper were introduced to investigate the change rules of surrounding rock deformation and tunnel safety factor, and the sensitivity of the safety factor of tunneling in swelling loess. Analysis results showed that the change rules of surrounding rock response curves and safety factors obtained by the models were consistent with the actual situation, and the predicted maximum radial displacement of free face was close to the measured value. These indicate that the models are applicable to the stability analysis of initial support of swelling loess tunnel.

EBOLA VIRUS DISEASE DYNAMICS WITH SOME PREVENTIVE MEASURES: A CASE STUDY OF THE 2018–2020 KIVU OUTBREAK

To fight against Ebola virus disease, several measures have been adopted. Among them, isolation, safe burial and vaccination occupy a prominent place. In this paper, we present a model which takes into account these three control strategies as well as the indirect transmission through a polluted environment. The asymptotic behavior of our model is achieved. Namely, we determine a threshold value [Formula: see text] of the control reproduction number [Formula: see text], below which the disease is eliminated in the long run. Whenever the value of [Formula: see text] ranges from [Formula: see text] and 1, we prove the existence of a backward bifurcation phenomenon, which corresponds to the case, where a locally asymptotically stable positive equilibrium co-exists with the disease-free equilibrium, which is also locally asymptotically stable. The existence of this bifurcation complicates the control of Ebola, since the requirement of [Formula: see text] below one, although necessary, is no longer sufficient for the elimination of Ebola, more efforts need to be deployed. When the value of [Formula: see text] is greater than one, we prove the existence of a unique endemic equilibrium, locally asymptotically stable. That is the disease may persist and become endemic. Numerically, we fit our model to the reported data for the 2018–2020 Kivu Ebola outbreak which occurred in Democratic Republic of Congo. Through the sensitivity analysis of the control reproduction number, we prove that the transmission rates of infected alive who are outside hospital are the most influential parameters. Numerically, we explore the usefulness of isolation, safe burial combined with vaccination and investigate the importance to combine the latter control strategies to the educational campaigns or/and case finding.

ROLE OF MEDIA COVERAGE IN MITIGATING AN EPIDEMIC OUTBREAK: AN OPTIMAL CONTROL MODEL

Flu is an acute respiratory infection caused by the influenza virus. The outbreak usually occurs every year in temperate region during the fall and winter seasons, but it is present year-round in tropics. Perceived risk of infection, affordability and lack of awareness among the population results in a low level of vaccination coverage. To control disease transmission and promote vaccination, public health officials use media coverage to spread awareness on vaccine safety, vaccine coverage, disease prevalence in the population through public health websites, advertisements, and other social media web pages. Media coverage acts as an incentive as it helps to decrease overall transmission potential and also at the same time increases the vaccination coverage in the population. Since the public health department has a limited budget, it needs to make optimum allocation of its effort to reduce the total cost of infection. Our paper investigates the effect of media coverage using SIR model of disease transmission. We look at three possible functional relationships — linear, exponential, and hyperbolic — the way media coverage may affect the disease transmission and vaccination rate. We derive necessary conditions of optimal solution using Optimal Control Theory and Pontryagin Maximum Principle (PMP) to minimize the total cost for infection. Analysis of our paper demonstrates that the cost of optimal management is four times less than the cost of constant control effort, and putting more effort into reducing transmission is optimal rather than an effort to increase vaccination at the beginning of the outbreak. Analysis of the role of media coverage under three different scenarios may help in formulating policies for public health programs in mitigating the influenza outbreak.

Acute Infection of Viral Pathogens and Their Innate Immune Escape

Viral infections can cause rampant disease in human beings, ranging from mild to acute, that can often be fatal unless resolved. An acute viral infection is characterized by sudden or rapid onset of disease, which can be resolved quickly by robust innate immune responses exerted by the host or, instead, may kill the host. Immediately after viral infection, elements of innate immunity, such as physical barriers, various phagocytic cells, group of cytokines, interferons (IFNs), and IFN-stimulated genes, provide the first line of defense for viral clearance. Innate immunity not only plays a critical role in rapid viral clearance but can also lead to disease progression through immune-mediated host tissue injury. Although elements of antiviral innate immunity are armed to counter the viral invasion, viruses have evolved various strategies to escape host immune surveillance to establish successful infections. Understanding complex mechanisms underlying the interaction between viruses and host’s innate immune system would help develop rational treatment strategies for acute viral infectious diseases. In this review, we discuss the pathogenesis of acute infections caused by viral pathogens and highlight broad immune escape strategies exhibited by viruses.

Mathematical modeling of COVID-19 infection dynamics in Ghana: Impact evaluation of integrated government and individual level interventions

The raging COVID-19 pandemic is arguably the most important threat to global health presently. Although there Although there is currently a a a vaccine, preventive measures have been proposed to reduce the spread of infection but the efficacy of these interventions, and their likely impact on the number of COVID-19 infections is unknown. In this study, we proposed the SEIQHRS model (susceptible-exposed-infectious-quarantine-hospitalized-recovered-susceptible) model that predicts the trajectory of the epidemic to help plan an effective control strategy for COVID-19 in Ghana. We provided a short-term forecast of the early phase of the epidemic trajectory in Ghana using the generalized growth model. We estimated the effective basic Reproductive number Re in real-time using three different estimation procedures and simulated worse case epidemic scenarios and the impact of integrated individual and government interventions on the epidemic in the long term using compartmental models. The maximum likelihood estimates of Re and the corresponding 95% confidence interval was 2.04 [95% CI: 1.82-2.27; 12th March-7th April 2020]. The Re estimate using the exponential growth method was 2.11 [95% CI: 2.00-2.24] within the same period. The Re estimate using time-dependent (TD) method showed a gradual decline of the Effective Reproductive Number since March 12, 2020 when the first 2 index cases were recorded but the rate of transmission remains high (TD: Re = 2.52; 95% CI: [1.87-3.49]). The current estimate of Re based on the TD method is 1.74 [95% CI: 1.41-2.10; (13th May 2020)] but with comprehensive integrated government and individual level interventions, the Re could reduce to 0.5 which is an indication of the epidemic dying out in the general population. Our results showed that enhanced government and individual-level interventions and the intensity of media coverage could have a substantial effect on suppressing transmission of new COVID-19 cases and reduced death rates in Ghana until such a time that a potent vaccine or drug is discovered.

Management practices of emergency departments in general hospitals based on blockage of chain of infection during a COVID-19 epidemic

In a Coronavirus disease 2019 (COVID-19) epidemic, management of the emergency department is a difficult task in terms of prevention and control of the disease in general hospitals. On top of meeting urgent needs of patients for medical treatment, the emergency department also has to devote resources into investigation and prevention of COVID-19. At the beginning of the epidemic, with the strategy to intercept the chain of infection, Peking University First Hospital (PKUFH) focused on three important aspects: controlling the source of infection, cutting off the route of transmission, and protecting vulnerable populations, to expeditiously draft scientific and proper management measures for the emergency department, followed by real-time dynamic adjustments based on the development trend of the epidemic. These measures effectively ensured a smooth, orderly and safe operation of the emergency department. As of the writing of this manuscript, there has been no active COVID-19 infection in patients and medical staff in the emergency department, and no infection in patients admitted to PKUFH through the emergency department. This study describes the prevention and control measures in the emergency department of PKUFH during the outbreak of COVID-19, aiming to provide some reference for domestic and international medical institutions.

Estimating the protective effect of case isolation with transmission tree reconstruction during the Ebola outbreak in Nigeria, 2014

The mainstream interventions used during the 2014-2016 Ebola epidemic were contact tracing and case isolation. The Ebola outbreak in Nigeria that formed part of the 2014-2016 epidemic demonstrated the effectiveness of control interventions with a 100% hospitalization rate. Here, we aim to explicitly estimate the protective effect of case isolation, reconstructing the time events of onset of illness and hospitalization as well as the transmission network. We show that case isolation reduced the reproduction number and shortened the serial interval. Employing Bayesian inference with the Markov chain Monte Carlo method for parameter estimation and assuming that the reproduction number exponentially declines over time, the protective effect of case isolation was estimated to be 39.7% (95% credible interval: 2.4%-82.1%). The individual protective effect of case isolation was also estimated, showing that the effectiveness was dependent on the speed, i.e. the time from onset of illness to hospitalization.

Transmission Dynamics and Control Mechanisms of Vector-Borne Diseases with Active and Passive Movements Between Urban and Satellite Cities

A metapopulation model which explicitly integrates vector-borne and sexual transmission of an epidemic disease with passive and active movements between an urban city and a satellite city is formulated and analysed. The basic reproduction number of the disease is explicitly determined as a combination of sexual and vector-borne transmission parameters. The sensitivity analysis reveals that the disease is primarily transmitted via the vector-borne mode, rather than via sexual transmission, and that sexual transmission by itself may not initiate or sustain an outbreak. Also, increasing the population movements from one city to the other leads to an increase in the basic reproduction number of the later city but a decrease in the basic reproduction number of the former city. The influence of other significant parameters is also investigated via the analysis of suitable partial rank correlation coefficients. After gauging the effects of mobility, we explore the potential effects of optimal control strategies relying upon several distinct restrictions on population movement.

Accurate forecasts of the effectiveness of interventions against Ebola may require models that account for variations in symptoms during infection

Epidemiological models are routinely used to predict the effects of interventions aimed at reducing the impacts of Ebola epidemics. Most models of interventions targeting symptomatic hosts, such as isolation or treatment, assume that all symptomatic hosts are equally likely to be detected. In other words, following an incubation period, the level of symptoms displayed by an individual host is assumed to remain constant throughout an infection. In reality, however, symptoms vary between different stages of infection. During an Ebola infection, individuals progress from initial non-specific symptoms through to more severe phases of infection. Here we compare predictions of a model in which a constant symptoms level is assumed to those generated by a more epidemiologically realistic model that accounts for varying symptoms during infection. Both models can reproduce observed epidemic data, as we show by fitting the models to data from the ongoing epidemic in the Democratic Republic of the Congo and the 2014-16 epidemic in Liberia. However, for both of these epidemics, when interventions are altered identically in the models with and without levels of symptoms that depend on the time since first infection, predictions from the models differ. Our work highlights the need to consider whether or not varying symptoms should be accounted for in models used by decision makers to assess the likely efficacy of Ebola interventions.

Effect of sexual transmission on the West Africa Ebola outbreak in 2014: a mathematical modelling study

The outbreak of the Ebola virus has resulted in significant morbidity and mortality in the affected areas, and Ebola virus RNA has been found in the semen of the survivors after 9 months of symptom onset. However, the role that sexual transmission played in the transmission is not very clear. In this paper, we developed a compartmental model for Ebola virus disease (EVD) dynamics, which includes three different infectious routes: contact with the infectious, contact with dead bodies, and transmission by sexual behaviour with convalescent survivors. We fitted the model to daily cumulative cases from the first reported infected case to October 25, 2014 for the epidemic in Sierra Leone, Liberia and Guinea. The basic reproduction numbers in these countries were estimated as 1.6726 (95%CI:1.5922–1.7573), 1.8162 (95%CI:1.7660–1.8329) and 1.4873 (95%CI:1.4770–1.4990), respectively. We calculated the contribution of sexual transmission to the basic reproduction number R₀ as 0.1155 (6.9%), 0.0236 (2.8%) and 0.0546 (3.7%) in Sierra Leone, Liberia and Guinea, respectively. Sensitivity analysis shows that the transmission rates caused by contacts with alive patients and sexual activities with convalescent patients have stronger impacts on the R₀. These results suggest that isolating the infectious individuals and advising the recovery men to avoid sexual intercourse are efficient ways for the eradication of endemic EVD.

Efficacy of control measures in the control of Ebola, Liberia 2014-2015

The largest outbreak of Ebola to date is the 2014 West Africa Ebola outbreak, with more than 10,000 cases and over 4000 deaths reported in Liberia alone. To control the spread of the outbreak, multiple interventions were implemented: identification and isolation of cases, contact tracing, quarantining of suspected contacts, proper personal protection, safely conducted burials, improved education, social awareness and individual protective measures. Devising rigorous methodologies for the evaluation of the effectiveness of the control measures implemented to stop an outbreak is of paramount importance. In this paper, we evaluate the effectiveness of the 2014 Ebola outbreak interventions. We rely on model selection to determine the best model that explains the 2014 Ebola outbreak data in Liberia which is the simplest model with a social distancing term. We couple structural and practical identifiability analysis with the computation of confidence intervals to pinpoint the uncertainty in the parameter estimations. Finally, we evaluate the efficacy of control measures using the Ebola model with social distancing. Among all the control measures, we find that social distancing had the most impact on the control of the 2014 Ebola epidemic in Libreria followed by isolation and quarantining.

A Predictive Spatial Distribution Framework for Filovirus-Infected Bats

Tools with predictive capabilities in regards of filovirus outbreaks are mainly anthropocentric and have disregarded the ecological dimension of the problem. Here we contribute to shift the current paradigm by studying the dynamics of the putative main zoonotic niche of filoviruses, bats, and its link to environmental drivers. We propose a framework that combines data analysis, modeling, and the evaluation of sources of variability. We implement a regression analysis using factual data to correlate environmental parameters and the presence of bats to find the distribution of resources. The information inferred by the regression is fed into a compartmental model that describes the infection state. We also account for the lack of knowledge of some parameters using a sampling/averaging technique. As a result we estimate the spatio-temporal densities of bats. Importantly, we show that our approach is able to predict where and when an outbreak is likely to appear when tested against recent epidemic data in the context of Ebola. Our framework highlights the importance of considering the feedback between the ecology and the environment in zoonotic models and sheds light on the mechanisms to propagate filoviruses geographically. We expect that our methodology can help to design prevention policies and be used as a predictive tool in the context of zoonotic diseases associated to filoviruses.

Strategy and technology to prevent hospital-acquired infections: Lessons from SARS, Ebola, and MERS in Asia and West Africa

Hospital-acquired infections (HAIs) are serious problems for healthcare systems, especially in developing countries where public health infrastructure and technology for infection preventions remain undeveloped. Here, we characterized how strategy and technology could be mobilized to improve the effectiveness of infection prevention and control in hospitals during the outbreaks of Ebola, Middle East respiratory syndrome (MERS), and severe acute respiratory syndrome (SARS) in Asia and West Africa. Published literature on the hospital-borne outbreaks of SARS, Ebola, and MERS in Asia and West Africa was comprehensively reviewed. The results showed that healthcare systems and hospital management in affected healthcare facilities had poor strategies and inadequate technologies and human resources for the prevention and control of HAIs, which led to increased morbidity, mortality, and unnecessary costs. We recommend that governments worldwide enforce disaster risk management, even when no outbreaks are imminent. Quarantine and ventilation functions should be taken into consideration in architectural design of hospitals and healthcare facilities. We also recommend that health authorities invest in training healthcare workers for disease outbreak response, as their preparedness is essential to reducing disaster risk.

Considerations for use of Ebola vaccine during an emergency response

Vaccination against Ebola virus disease is a tool that may limit disease transmission and deaths in future outbreaks, integrated within traditional Ebola outbreak prevention and control measures. Although a licensed Ebolavirus vaccine (EV) is not yet available, the 2014-2016 West African Ebola outbreak has accelerated EV clinical trials and given public health authorities in Guinea, Liberia, and Sierra Leone experience with implementation of emergency ring vaccination. As evidence supporting the use of EV during an outbreak response has become available, public health authorities in at-risk countries are considering how to integrate EV into future emergency Ebola responses and for prevention in high-risk groups, such as healthcare workers and frontline workers (HCW/FLWs), even before an EV is licensed. This review provides an overview of Ebola epidemiology, immunology, and evidence to inform regional and country-level decisions regarding EV delivery during an emergency response and to at-risk populations before a licensed vaccine is available and beyond. Countries or regions planning to use EV will need to assess factors such as the likelihood of a future Ebolavirus outbreak, the most likely species to cause an outbreak, the availability of a safe and effective EV (unlicensed or licensed) for the affected population, capacity to implement Ebola vaccination in conjunction with standard Ebola outbreak control measures, and availability of minimum essential resources and regulatory requirements to implement emergency Ebola vaccination. Potential emergency vaccination strategies for consideration include ring or geographically targeted community vaccination, HCW/FLW vaccination, and mass vaccination. The development of guidelines and protocols for Ebola vaccination will help ensure that activities are standardized, evidence-based, and well-coordinated with overall Ebola outbreak response efforts in the future.

Modeling the role of public health education in Ebola virus disease outbreaks in Sudan

Public involvement in Ebola Virus Disease (EVD) prevention efforts is key to reducing disease outbreaks. Targeted education through practical health information to particular groups and sub-populations is crucial to controlling the disease. In this paper, we study the dynamics of Ebola virus disease in the presence of public health education with the aim of assessing the role of behavior change induced by health education to the dynamics of an outbreak. The power of behavior change is evident in two outbreaks of EVD that took place in Sudan only 3 years apart. The first occurrence was the first documented outbreak of EVD and produced a significant number of infections. The second outbreak produced far fewer cases, presumably because the population in the region learned from the first outbreak. We derive a system of ordinary differential equations to model these two contrasting behaviors. Since the population in Sudan learned from the first outbreak of EVD and changed their behavior prior to the second outbreak, we use data from these two instances of EVD to estimate parameters relevant to two contrasting behaviors. We then simulate a future outbreak of EVD in Sudan using our model that contains two susceptible populations, one being more informed about EVD. Our finding show how a more educated population results in fewer cases of EVD and highlights the importance of ongoing public health education.

Modeling the Ebola zoonotic dynamics: Interplay between enviroclimatic factors and bat ecology

Understanding Ebola necessarily requires the characterization of the ecology of its main enzootic reservoir, i.e. bats, and its interplay with seasonal and enviroclimatic factors. Here we present a SIR compartmental model where we implement a bidirectional coupling between the available resources and the dynamics of the bat population in order to understand their migration patterns. Our compartmental modeling approach and simulations include transport terms to account for bats mobility and spatiotemporal climate variability. We hypothesize that environmental pressure is the main driving force for bats' migration and our results reveal the appearance of sustained migratory waves of Ebola virus infected bats coupled to resources availability. Ultimately, our study can be relevant to predict hot spots of Ebola outbreaks in space and time and suggest conservation policies to mitigate the risk of spillovers.

Estimating the number of secondary Ebola cases resulting from an unsafe burial and risk factors for transmission during the West Africa Ebola epidemic

BACKGROUND

Safely burying Ebola infected individuals is acknowledged to be important for controlling Ebola epidemics and was a major component of the 2013-2016 West Africa Ebola response. Yet, in order to understand the impact of safe burial programs it is necessary to elucidate the role of unsafe burials in sustaining chains of Ebola transmission and how the risk posed by activities surrounding unsafe burials, including care provided at home prior to death, vary with human behavior and geography.

METHODOLOGY/PRINCIPAL FINDINGS

Interviews with next of kin and community members were carried out for unsafe burials in Sierra Leone, Liberia and Guinea, in six districts where the Red Cross was responsible for safe and dignified burials (SDB). Districts were randomly selected from a district-specific sampling frame comprised of villages and neighborhoods that had experienced cases of Ebola. An average of 2.58 secondary cases were potentially generated per unsafe burial and varied by district (range: 0-20). Contact before and after death was reported for 142 (46%) contacts. Caregivers of a primary case were 2.63 to 5.92 times more likely to become EVD infected compared to those with post-mortem contact only. Using these estimates, the Red Cross SDB program potentially averted between 1,411 and 10,452 secondary EVD cases, reducing the epidemic by 4.9% to 36.5%.

CONCLUSIONS/SIGNIFICANCE

SDB is a fundamental control measure that limits community transmission of Ebola; however, for those individuals having contact before and after death, it was impossible to ascertain the exposure that caused their infection. The number of infections prevented through SDB is significant, yet greater impact would be achieved by early hospitalization of the primary case during acute illness.

A systematic review of early modelling studies of Ebola virus disease in West Africa

Phenomenological and mechanistic models are widely used to assist resource planning for pandemics and emerging infections. We conducted a systematic review, to compare methods and outputs of published phenomenological and mechanistic modelling studies pertaining to the 2013-2016 Ebola virus disease (EVD) epidemics in four West African countries - Sierra Leone, Liberia, Guinea and Nigeria. We searched Pubmed, Embase and Scopus databases for relevant English language publications up to December 2015. Of the 874 articles identified, 41 met our inclusion criteria. We evaluated these selected studies based on: the sources of the case data used, and modelling approaches, compartments used, population mixing assumptions, model fitting and calibration approaches, sensitivity analysis used and data bias considerations. We synthesised results of the estimated epidemiological parameters: basic reproductive number (R 0), serial interval, latent period, infectious period and case fatality rate, and examined their relationships. The median of the estimated mean R 0 values were between 1·30 and 1·84 in Sierra Leone, Liberia and Guinea. Much higher R 0 value of 9·01 was described for Nigeria. We investigated several issues with uncertainty around EVD modes of transmission, and unknown observation biases from early reported case data. We found that epidemic models offered R 0 mean estimates which are country-specific, but these estimates are not associating with the use of several key disease parameters within the plausible ranges. We find simple models generally yielded similar estimates of R 0 compared with more complex models. Models that accounted for data uncertainty issues have offered a higher case forecast compared with actual case observation. Simple model which offers transparency to public health policy makers could play a critical role for advising rapid policy decisions under an epidemic emergency.

Pandemic Risk Modelling

This chapter will explore the nature of communicable diseases, a brief history of pandemics, and will introduce the mathematical models used to evaluate the risk pandemics pose to human populations. Such modelling is used in a public health context, where modelling past and current events provides insight in how to respond most effectively to a new outbreak. It is also used in the context of risk mutualisation and transfer. As recently as 2013, a survey of 30,000 insurance executives placed global pandemic as the biggest extreme risk facing insurers (Towers Watson. 2013. Insurers Rate Global Pandemic as the Major Extreme Risk. 3 December). The chapter will introduce the principles used to model these events in the insurance industry and will conclude with a review of the way these models are applied in an unconventional risk transfer context.

Dynamic modelling of strategies for the control of acute haemorrhagic conjunctivitis outbreaks in schools in Changsha, China (2004–2015)

Outbreaks of acute haemorrhagic conjunctivitis (AHC) – a rapidly progressing and highly contagious infection – often occur in schools during summer and autumn. We used dynamic modelling to evaluate the efficacy of interventions to control AHC outbreaks in schools. A susceptible-infected-recovered (SIR) model was built to simulate AHC outbreaks in Chinese schools, with isolation or school closure added into the model. We used outbreak data from the period 2004–2015 in our models to estimate the effective reproduction number and assess the efficacy of interventions. The median effective reproduction number (uncontrolled) of AHC outbreaks was 7·00 (range 1·77–25·87). The median effective reproduction number (controlled) of AHC outbreaks was 0·16 (range 0·00–2·28). Intervention efficacy is affected by the timing of isolation; earlier isolation is associated with a lower morbidity peak and smaller total attack rate (TAR). School closures were not effective; TARs were almost 100% and did not change even when different school closure durations were adopted. Isolation and school closure as a combined intervention strategy was used to simulate outbreak control, but the efficacy was the same as isolation alone. An isolation programme could be an effective primary intervention during AHC outbreaks in schools. However, school closure is not recommended.

A one-year effective reproduction number of the 2014-2015 Ebola outbreaks in the widespread West African countries and quantitative evaluation of air travel restriction measure

BACKGROUND

The 2014-2015 Ebola outbreak in West Africa is the largest and longest Ebola Virus Disease (EVD) outbreak in the history, and the virus has escaped across countries and continents via air travel in this outbreak.

METHOD

The interpolated data from WHO Ebola situation reports were used to estimate number of weekly infectious individuals and daily effective reproduction numbers (R_t) in Guinea, Liberia and Sierra Leone. A stochastic dynamic model was performed to estimate the risk of EVD importation into the top 20 final destination countries of air travelers departing from within the three epidemic countries, and the effectiveness of air travel restriction was subsequently evaluated.

RESULTS

The daily R_t was estimated at 0.72-1.32 in Guinea, 0.62-1.38 in Liberia and 0.81-1.38 in Sierra Leone. The peak of EVD importation probability was observed in early November 2014 and the restriction of air travel may mitigate the risk up to 67.7% (95% CI 66.6-68.7).

CONCLUSIONS

Our results suggest that restriction of air travels is effective in reducing the risk of EVD importation but controlling of the virus at the original affected countries is vitally more important for preventing inter-terrestrial dissemination of EVD.

The role of interconnectivity in control of an Ebola epidemic

Several West African countries - Liberia, Sierra Leone and Guinea - experienced significant morbidity and mortality during the largest Ebola epidemic to date, from late 2013 through 2015. The extent of the epidemic was fueled by outbreaks in large urban population centers as well as movement of the pathogen between populations. During the epidemic there was no known vaccine or drug, so effective disease control required coordinated efforts that include both standard medical and community practices such as hospitalization, quarantine and safe burials. Due to the high connectivity of the region, control of the epidemic not only depended on internal strategies but also was impacted by neighboring countries. In this paper, we use a deterministic framework to examine the role of movement between two populations in the overall success of practices designed to minimize the extent of Ebola epidemics. We find that it is possible for even small amounts of intermixing between populations to positively impact the control of an epidemic on a more global scale.