Transmission dynamics and control of Ebola virus disease outbreak in Nigeria, July to September 2014

A beta-Poisson model for infectious disease transmission

Outbreaks of emerging and zoonotic infections represent a substantial threat to human health and well-being. These outbreaks tend to be characterised by highly stochastic transmission dynamics with intense variation in transmission potential between cases. The negative binomial distribution is commonly used as a model for transmission in the early stages of an epidemic as it has a natural interpretation as the convolution of a Poisson contact process and a gamma-distributed infectivity. In this study we expand upon the negative binomial model by introducing a beta-Poisson mixture model in which infectious individuals make contacts at the points of a Poisson process and then transmit infection along these contacts with a beta-distributed probability. We show that the negative binomial distribution is a limit case of this model, as is the zero-inflated Poisson distribution obtained by combining a Poisson-distributed contact process with an additional failure probability. We assess the beta-Poisson model's applicability by fitting it to secondary case distributions (the distribution of the number of subsequent cases generated by a single case) estimated from outbreaks covering a range of pathogens and geographical settings. We find that while the beta-Poisson mixture can achieve a closer to fit to data than the negative binomial distribution, it is consistently outperformed by the negative binomial in terms of Akaike Information Criterion, making it a suboptimal choice on parsimonious grounds. The beta-Poisson performs similarly to the negative binomial model in its ability to capture features of the secondary case distribution such as overdispersion, prevalence of superspreaders, and the probability of a case generating zero subsequent cases. Despite this possible shortcoming, the beta-Poisson distribution may still be of interest in the context of intervention modelling since its structure allows for the simulation of measures which change contact structures while leaving individual-level infectivity unchanged, and vice-versa.

Inequitable access to Ebola vaccines and the resurgence of Ebola in Africa: A state of arts review

The Ebola virus, a member of the filoviridae family of viruses, is responsible for causing Ebola Virus Disease (EVD) with a case fatality rate as high as 50%. The largest EVD outbreak was recorded in West Africa from March 2013 to June 2016, leading to over 28 000 cases and 11 000 deaths. It affected several countries, including Nigeria, Senegal, Guinea, Liberia, and Sierra Leone. Until then, EVD was predominantly reported in remote villages in central and west Africa close to tropical rainforests. Human mobility, behavioral and cultural norms, the use of bushmeat, burial customs, preference for traditional remedies and treatments, and resistance to health interventions are just a few of the social factors that considerably aid and amplify the risk of transmission. The scale and persistence of recent ebola outbreaks, as well as the risk of widespread global transmission and its ability for bioterrorism, have led to a rethinking of public health strategies to curb the disease, such as the expedition of Ebola vaccine production. However, as vaccine production lags in the subcontinent, among other challenges, the risk of another ebola outbreak is likely and feared by public health authorities in the region. This review describes the inequality of vaccine production in Africa and the resurgence of EVD, emphasizing the significance of health equality.

Combating the zoonotic trio of Ebola virus disease, Lassa fever, and COVID-19 in Nigeria: a retrospection of the challenges and lessons

Various infectious disease outbreaks linked to zoonotic sources have been recorded over the years, some of which have resulted in epidemics on a national, regional, or global scale. In Africa, a number of such outbreaks occur intermittently, especially in countries like Nigeria with a high-risk of epidemiological transmission. Three viral outbreaks with zoonotic links have hit the Nigerian healthcare system hardest, which are the Ebola virus disease, Lassa fever and Coronavirus disease 2019. Due to the fragile nature of the Nigerian health system, several challenges were encountered in the process of responding to these viral outbreaks, some of which included inadequate healthcare infrastructure, limited diagnostic capacity, unfledged nature of emergency response, unsatisfactory remuneration of health workers, misinformation trends, amongst others. By reminiscing on the challenges and lessons learnt from these viral disease outbreaks, the Nigerian government and policymakers will be able to adopt more effective approaches towards emergency preparedness for future outbreaks of infectious diseases.

Knowledge, Attitudes and Practices Assessment on Bat-Borne Zoonotic Diseases Among the People of Moyamba District, Sierra Leone

Background

Bats are considered wildlife species of public health concern, as they are known to host various pathogenic agents, and their interactions with humans are potential routes of pathogen spillover. A high level of knowledge on Bat-borne Zoonotic Diseases (BZD), their causative agents, signs, symptoms, mode and pattern of transmission, health attitudes, and practices towards the disorders are vital parameters in handling them. This study aimed to look into BZD knowledge, public attitudes, and behaviour.

Methods

 We surveyed the 14 chiefdoms of Moyamba district. A total of 421 participants were randomly sampled using closed-ended questionnaire. Simple linear regression analysis was used to determine the effects of gender, age, education, and livelihood opportunities on BZD knowledge (at 95% confidence interval and alpha value = 0.05). The findings were analysed and correlated with a scientific and public health perspective to assess the breadth of knowledge and awareness of BZD among the people of Moyamba district.

Results

The findings from the study show a low level of knowledge on BZD among the people of the Moyamba district, with only 119 (28.3%) individuals that had some knowledge about BZD. Of those that knew about BZD, 94 (79.0%) had very little knowledge, 24 (20.2%) had a fair amount, and 1 (0.8%) had a great deal of knowledge about BZD. The primary mode of knowledge dissemination was through social media platforms.

Conclusion

The level of knowledge about BZD is also very low. As a result of these findings, policymakers, health professionals, and environmental educators will be compelled to develop strategies to reduce the risk of BZD transmission in Sierra Leone's population.

Modelling the impact of some control strategies on the transmission dynamics of Ebola virus in human-bat population: An optimal control analysis

Qualitative research and comprehensive public awareness to nip the transmission of Ebola virus in the bud before it becomes a global threat is fast becoming imperative especially now that the Gambia Ebola virus is mutated. It is therefore necessary to consider and investigate a vector-host transmission model for possible control strategy of this deadly disease. Hence, in this study, we presented a novel and feasible human-bat (host-vector) S h E h I h R h i s R h n i - S b E b I b model which foretells the spread and severity of the Ebola virus from bats to humans to investigate the combined effects of three control strategies viz: (1) allowing specialized and designated agencies to bury deceased from Ebola infection without relatives touching or curdling the remains as usually practiced in most part of Africa as last respect for their departed love ones ( k 1 ), (2) systematic and deliberate depopulation of bats in the metropolis (through persecution with pesticide exposure, pre capturing, chemical timber treatment for roosts destruction) to discourage hunting them for food by virtue of their proximity ( k 2 ) and (3) immediate treatment of infected individuals in isolation ( k 3 ). We established, among others, the endemic equilibrium, disease-free equilibrium, global and local stability, non-negativity, and boundedness of the model to prove the epidemiological feasibility of the model. The reality of the presence of optimal control remarkably influences the dynamics of transmission of the virus and simulated results also confirm the great effect of the combination of the control strategies k 1 , k 2 and k 3 in flattening the curve of Ebola transmission (fig 1 - fig 8). Health workers and policy makers are better informed with fundamental precautions that could help eradicate Ebola from the populace.

The doubling effect of COVID-19 cases on key health indicators

From the beginning of the COVID-19 pandemic, researchers advised policy makers to make informed decisions towards the adoption of mitigating interventions. Key easy-to-interpret metrics applied over time can measure the public health impact of epidemic outbreaks. We propose a novel method which quantifies the effect of hospitalizations or mortality when the number of COVID-19 cases doubles. Two analyses are used, a country-by-country analysis and a multi-country approach which considers all countries simultaneously. The new measure is applied to several European countries, where the presence of different variants, vaccination rates and intervention measures taken over time leads to a different risk. Based on our results, the vaccination campaign has a clear effect for all countries analyzed, reducing the risk over time. However, the constant emergence of new variants combined with distinct intervention measures impacts differently the risk per country.

Bridging Animal and Human Data in Pursuit of Vaccine Licensure

The FDA Animal Rule was devised to facilitate approval of candidate vaccines and therapeutics using animal survival data when human efficacy studies are not practical or ethical. This regulatory pathway is critical for candidates against pathogens with high case fatality rates that prohibit human challenge trials, as well as candidates with low and sporadic incidences of outbreaks that make human field trials difficult. Important components of a vaccine development plan for Animal Rule licensure are the identification of an immune correlate of protection and immunobridging to humans. The relationship of vaccine-induced immune responses to survival after vaccination and challenge must be established in validated animal models and then used to infer predictive vaccine efficacy in humans via immunobridging. The Sabin Vaccine Institute is pursuing licensure for candidate filovirus vaccines via the Animal Rule and has convened meetings of key opinion leaders and subject matter experts to define fundamental components for vaccine licensure in the absence of human efficacy data. Here, filoviruses are used as examples to review immune correlates of protection and immunobridging. The points presented herein reflect the presentations and discussions during the second meeting held in October 2021 and are intended to address important considerations for developing immunobridging strategies.

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.

Superspreading is one of the key transmission features of many infectious diseases and is considered a consequence of the heterogeneity in infectiousness of individual cases. To characterize the superspreading potential, we divided individual infectiousness into two independent and additive components, including a fixed baseline and a variable part. Such decomposition produced an improvement in the fit of the model explaining the distribution of real-world datasets of COVID-19 and SARS that can be captured by the classic statistical tests. Disease control strategies may be developed by monitoring the characteristics of superspreading. For the COVID-19 pandemic, population-wide interventions are suggested first to limit the transmission at a scale of general population, and then high-risk-specific control strategies are recommended subsequently to lower the risk of superspreading.

Situation assessment and natural dynamics of COVID-19 pandemic in Nigeria, 31 May 2020

Background

The coronavirus disease (COVID-19) remains a global public health issue due to its high transmission and case fatality rate. There is apprehension on how to curb the spread and mitigate the socio-economic impacts of the pandemic, but timely and reliable daily confirmed cases' estimates are pertinent to the pandemic's containment. This study therefore conducted a situation assessment and applied simple predictive models to explore COVID-19 progression in Nigeria as at 31 May 2020.

Methods

Data used for this study were extracted from the websites of the European Centre for Disease Control (World Bank data) and Nigeria Centre for Disease Control. Besides descriptive statistics, four predictive models were fitted to investigate the pandemic natural dynamics.

Results

The case fatality rate of COVID-19 was 2.8%. A higher number of confirmed cases of COVID-19 was reported daily after the relaxation of lockdown than before and during lockdown. Of the 36 states in Nigeria, including the Federal Capital Territory, 35 have been affected with COVID-19. Most active cases were in Lagos (n = 4064; 59.2%), followed by Kano (n = 669; 9.2%). The percentage of COVID-19 recovery in Nigeria (29.5%) was lower compared to South Africa (50.3%), but higher compared to Kenya (24.1%). The cubic polynomial model had the best fit. The projected value for COVID-19 cumulative cases for 30 June 2020 in Nigeria was 27,993 (95% C.I: 27,001–28,986).

Conclusion

The daily confirmed cases of COVID-19 are increasing in Nigeria. Increasing testing capacity for the disease may further reveal more confirmed cases. As observed in this study, the cubic polynomial model currently offers a better prediction of the future COVID-19 cases in Nigeria.

Impact of recurrent outbreaks of Ebola virus disease in Africa: a meta-analysis of case fatality rates

OBJECTIVES

Between 2010 and 2020, Africa witnessed several outbreaks of Ebola virus disease (EVD), each presenting with varying case fatality rate (CFR) and other socio-economic impacts. This study aims to summarize the CFR and identify potential factors that influenced the severity of EVD outbreaks in Africa.

STUDY DESIGN

This was a systematic review and meta-analysis of EVD outbreaks published between January 2010 and March 2020, using Web of Science, Scopus, and PubMed databases.

METHODS

Only English-language articles and reports, including the number of cases and deaths during the outbreak in Africa, were considered. The quality of the included articles was assessed using Murad's quality assessment tool. The analysis was conducted using Stata (version 12), pooled effect sizes were calculated using the random-effects model, and heterogeneity was tested for using the I² statistic.

RESULTS

Thirteen studies with 32,300 cases and 13,727 deaths were identified, whose pooled CFR was 60% (95% confidence interval [CI]: 47-73%). The most EVD-affected countries were the Democratic Republic of Congo with five outbreaks and a pooled CFR of 65% (95% CI: 59-71%), followed by Uganda with three outbreaks and CFR of 83% (95% CI: 60-99%). Zaire ebolavirus caused the most outbreaks (10), with a CFR of 58% (95% CI: 45-71%). Besides, outbreaks with fewer than 1000 cases reported a higher CFR rate (65%, 95% CI: 54-75%) compared with those with more cases (51%, 95% CI: 33-69%).

CONCLUSION

The study has revealed a considerably high CFR caused by the recurrent EVD outbreaks in Africa. It also notes an implementation gap in the prevention and control strategies and thus identifies a need to strengthen the surveillance systems and response mechanisms to enable early detection and prompt control of future outbreaks.

Postexposure Prophylaxis With rVSV-ZEBOV Following Exposure to a Patient With Ebola Virus Disease Relapse in the United Kingdom: An Operational, Safety, and Immunogenicity Report

Background

In October 2015, 65 people came into direct contact with a healthcare worker presenting with a late reactivation of Ebola virus disease (EVD) in the United Kingdom. Vaccination was offered to 45 individuals with an initial assessment of high exposure risk.

Methods

Approval for rapid expanded access to the recombinant vesicular stomatitis virus–Zaire Ebola virus (rVSV-ZEBOV) vaccine as an unlicensed emergency medicine was obtained from the relevant authorities. An observational follow-up study was carried out for 1 year following vaccination.

Results

Twenty-six of 45 individuals elected to receive vaccination between 10 and 11 October 2015 following written informed consent. By day 14, 39% had seroconverted, increasing to 87% by day 28 and 100% by 3 months, although these responses were not always sustained. Neutralizing antibody responses were detectable in 36% by day 14 and 73% at 12 months. Common side effects included fatigue, myalgia, headache, arthralgia, and fever. These were positively associated with glycoprotein-specific T-cell but not immunoglobulin (Ig) M or IgG antibody responses. No severe vaccine-related adverse events were reported. No one exposed to the virus became infected.

Conclusions

This paper reports the use of the rVSV-ZEBOV vaccine given as an emergency intervention to individuals exposed to a patient presenting with a late reactivation of EVD. The vaccine was relatively well tolerated, but a high percentage developed a fever ≥37.5°C, necessitating urgent screening for Ebola virus, and a small number developed persistent arthralgia.

Mathematical and Statistical Analysis of Doubling Times to Investigate the Early Spread of Epidemics: Application to the COVID-19 Pandemic

Simple mathematical tools are needed to quantify the threat posed by emerging and re-emerging infectious disease outbreaks using minimal data capturing the outbreak trajectory. Here we use mathematical analysis, simulation and COVID-19 epidemic data to demonstrate a novel approach to numerically and mathematically characterize the rate at which the doubling time of an epidemic is changing over time. For this purpose, we analyze the dynamics of epidemic doubling times during the initial epidemic stage, defined as the sequence of times at which the cumulative incidence doubles. We introduce new methodology to characterize epidemic threats by analyzing the evolution of epidemics as a function of (1) the number of times the epidemic doubles until the epidemic peak is reached and (2) the rate at which the doubling times increase. In our doubling-time approach, the most dangerous epidemic threats double in size many times and the doubling times change at a relatively low rate (e.g., doubling times remain nearly invariant) whereas the least transmissible threats double in size only a few times and the doubling times rapidly increases in the period of emergence. We derive analytical formulas and test and illustrate our methodology using synthetic and COVID-19 epidemic data. Our mathematical analysis demonstrates that the series of epidemic doubling times increase approximately according to an exponential function with a rate that quantifies the rate of change of the doubling times. Our analytic results are in excellent agreement with numerical results. Our methodology offers a simple and intuitive approach that relies on minimal outbreak trajectory data to characterize the threat posed by emerging and re-emerging infectious diseases.

Modelling of optimal vaccination strategies in response to a bioterrorism associated smallpox outbreak

The reemergence of smallpox as a bioterrorism attack is now an increasing and legitimate concern. Advances in synthetic biology have now made it possible for the virus to be synthesized in a laboratory, with methods publicly available. Smallpox introduction into a susceptible population, with increased immunosuppression and an aging population, raises questions of how vaccination should be used in an epidemic situation when supply may be limited. We constructed three modified susceptible-latent-infectious-recovered (SEIR) models to simulate targeted, ring and mass vaccination in response to a smallpox outbreak in Sydney, Australia. We used age-specific distributions of susceptibility, infectivity, contact rates, and tested outputs under different assumptions. The number of doses needed of second- and third-generation vaccines are estimated, along with the total number of deaths at the end of the epidemic. We found a faster response is the key and ring vaccination of traced contacts is the most effective strategy and requires a smaller number of doses. However if public health authorities are unable to trace a high proportion of contacts, mass vaccination with at least 125,000 doses delivered per day is required. This study informs a better preparedness and response planning for vaccination in a case of a smallpox outbreak in a setting such as Sydney.

Ebola virus outbreak preparedness plan for developing Nations: Lessons learnt from affected countries

BACKGROUND

Ebola virus (EBOV); a public health emergency of international concern,is known to pose threat of global outbreaks. EBOV has spread in African continent and due to unchecked international travel, importation of cases has been reported in different countries. In this alarming scenario, developing countries need to evaluate and upgrade their preparedness plan to contain the spread of EBOV. The present review lays down the updated preparedness plan for developing countries to contain future EBOV outbreaks.

METHODS

The literature on EBOV outbreaks and preparedness strategies reported were searched on Pubmed and Google Scholar using the MeSH terms such as "Ebola virus disease, Epidemic, Outbreak, Imported case, Preparedness, Public health interventions" combined with Boolean operator (OR) for the period of 2011-2020. Additionally, World Health organization (WHO) and Centers for Disease Control & Prevention (CDC) websites were searched for the guidelines, reports, containment strategies, containment plan of countries, actions taken by countries and international partners, etc. RESULTS: The present review analyzed the EBOV outbreaks between 2011-2020 and containment strategies used by the affected countries. Based on the lessons learned from EBOV outbreaks and personal experience in infectious disease management, we have recommended a preparedness and response plan for EBOV containment in developing countries.

CONCLUSION

Developing countries are particularly vulnerable to major outbreaks of EBOV due to increased international travel and unchecked transmission. The recommended preparedness plan will help developing counties to contain EBOV outbreaks in future.

COVID-19 caseness: An epidemiologic perspective

The concept of caseness in the COVID-19 virus is important for early case finding and reporting. These are essential steps for prevention and control. This review defines and differentiates between types of cases and specifies the elements of each case definition in general with their application to COVID-19, where appropriate. These terms and their application are useful for the surveillance team, epidemiologists, clinicians, policy makers as well as the public in general.

Nonhuman primate to human immunobridging to infer the protective effect of an Ebola virus vaccine candidate

It has been proven challenging to conduct traditional efficacy trials for Ebola virus (EBOV) vaccines. In the absence of efficacy data, immunobridging is an approach to infer the likelihood of a vaccine protective effect, by translating vaccine immunogenicity in humans to a protective effect, using the relationship between vaccine immunogenicity and the desired outcome in a suitable animal model. We here propose to infer the protective effect of the Ad26.ZEBOV, MVA-BN-Filo vaccine regimen with an 8-week interval in humans by immunobridging. Immunogenicity and protective efficacy data were obtained for Ad26.ZEBOV and MVA-BN-Filo vaccine regimens using a fully lethal EBOV Kikwit challenge model in cynomolgus monkeys (nonhuman primates [NHP]). The association between EBOV neutralizing antibodies, glycoprotein (GP)-binding antibodies, and GP-reactive T cells and survival in NHP was assessed by logistic regression analysis. Binding antibodies against the EBOV surface GP were identified as the immune parameter with the strongest correlation to survival post EBOV challenge, and used to infer the predicted protective effect of the vaccine in humans using published data from phase I studies. The human vaccine-elicited EBOV GP-binding antibody levels are in a range associated with significant protection against mortality in NHP. Based on this immunobridging analysis, the EBOV GP-specific-binding antibody levels elicited by the Ad26.ZEBOV, MVA-BN-Filo vaccine regimen in humans will likely provide protection against EBOV disease.

Hybrid Modeling of Ebola Propagation

The Ebola virus disease (EVD) epidemic that occurred in West Africa between 2014-16 resulted in over 28,000 cases and 11,000 deaths - one of the deadliest to date. A generalized model of the spatiotemporal progression of EVD for Liberia, Guinea, and Sierra Leone in 2014-16 remains elusive. There is also a disconnect in the literature on which interventions are most effective in curbing disease progression. To solve these two key issues, we designed a hybrid agent-based and compartmental model that switches from one paradigm to the other on a stochastic threshold. We modeled disease progression with promising accuracy using WHO datasets.

Delayed recognition of Ebola virus disease is associated with longer and larger outbreaks

The average time required to detect an Ebola virus disease (EVD) outbreak following spillover of Ebola virus (EBOV) to a primary human case has remained essentially unchanged for over 40 years, with some of the longest delays in detection occurring in recent decades. In this review, our aim was to examine the relationship between delays in detection of EVD and the duration and size of outbreaks, and we report that longer delays are associated with longer and larger EVD outbreaks. Historically, EVD outbreaks have typically been comprised of less than 100 cases (median = 60) and have lasted less than 4 months (median = 118 days). The ongoing outbreak in Democratic Republic of the Congo, together with the 2013–2016 west Africa outbreak, are stark outliers amidst these trends and had two of the longest delays in detection on record. While significant progress has been made in the development of EVD countermeasures, implementation during EVD outbreaks is problematic. Thus, EVD surveillance must be improved by the broad deployment of modern diagnostic tools, as prompt recognition of EVD has the potential to stem early transmission and ultimately limit the duration and size of outbreaks.

Forecasting the 2014 West African Ebola Outbreak

In 2014–2015, a large Ebola outbreak afflicted Liberia, Guinea, and Sierra Leone. We performed a systematic review of 26 manuscripts, published between 2014 and April 2015, that forecasted the West African Ebola outbreak while it was occurring, and we derived implications for how results could be interpreted by policymakers. Forecasted case counts varied widely. An important determinant of forecast accuracy for case counts was how far into the future predictions were made. Generally, forecasts for less than 2 months into the future tended to be more accurate than those made for more than 10 weeks into the future. The exceptions were parsimonious statistical models in which the decay of the rate of spread of the pathogen among susceptible individuals was dealt with explicitly. The most important lessons for policymakers regarding future outbreaks, when using similar modeling results, are: 1) uncertainty of forecasts will be greater in the beginning of the outbreak; 2) when data are limited, forecasts produced by models designed to inform specific decisions should be used complementarily for robust decision-making (e.g., 2 statistical models produced the most reliable case-counts forecasts for the studied Ebola outbreak but did not enable understanding of interventions’ impact, whereas several compartmental models could estimate interventions’ impact but required unavailable data); and 3) timely collection of essential data is necessary for optimal model use.

Concealing Disease: Trade and Travel Barriers and the Timeliness of Outbreak Reporting

Slow outbreak reporting by states is a key challenge to effectively responding to global health emergencies like Zika, Ebola, and H1N1. Current policy focuses on improving domestic outbreak surveillance capacity globally in order to reduce reporting lags. However, governments also face economic and political incentives to conceal outbreaks, and these incentives largely are ignored in policy discussions. In spite of the policy implications for outbreak response, the "capacity" and "will" explanations have not been systematically examined. Analysis of a dataset coding the timeliness of outbreak reporting from 1996-2014 finds evidence that states' unwillingness to report-rather than just their inability-leads to delayed reporting. The findings suggest that though building surveillance capacity is critical, doing so may not be sufficient to reduce reporting lags. Policy aimed at encouraging rapid reporting must also mitigate the associated economic and political costs.

Ebola virus outbreak in North Kivu and Ituri provinces, Democratic Republic of Congo, and the potential for further transmission through commercial air travel

BACKGROUND

The 2018-2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces, Democratic Republic of Congo (DRC), continues to spread. The recent discovery of cases in Uganda and in Goma, a major city in the eastern DRC, raises concern for potential EVD transmission in distant locales via commercial air travel.

METHODS

We examined air travel patterns from the affected region with itinerary-level data from the International Air Transport Association for the year 2018 between July and October, inclusive. We focused on three scenarios: (i) travel from Beni airport, (ii) travel from Beni, Goma and Bunia airports and (iii) travel from Beni, Goma and Bunia, and Kigali airports. We evaluated country-level Infectious Disease Vulnerability Index (IDVI) scores for traveller destinations.

RESULTS

There were 2255 commercial air passengers departing from Beni Airport during the specified time frame, all with domestic destinations, and 55% of which were to Goma. A total of 29 777 passengers travelled from Beni, Bunia and Goma airports during this time frame, with most travel (94.6%) departing from Goma Airport. A total of 72.4% of passengers' final destination from these three airports were within the DRC, primarily to Kinshasa. There were 166 281 outbound passengers from Beni, Bunia, Goma and Kigali airports with the majority (82.1%) of passengers departing from Kigali. The most frequent destinations from these airports were Nairobi, Kinshasa and Entebbe. Eight of the 10 destinations with greatest passenger volumes are to countries with IDVI scores less than 0.4.

CONCLUSION

There is little commercial airline connectivity from the current EVD-affected area; however, larger cities in DRC and throughout East Africa should be aware of the low potential for EVD importation through this route. Most countries at greatest risk for EVD importation have limited capacity to manage these cases.

Infection Rates and Risk Factors for Infection Among Health Workers During Ebola and Marburg Virus Outbreaks: A Systematic Review

Background

Infection in health workers (HWs) has characterized outbreaks of Ebola virus disease (EVD) and Marburg virus disease (MVD). We conducted a systematic review to investigate infection and mortality rates and common exposure risks in HWs in EVD and MVD outbreaks.

Methods

We searched the EMBASE and PubMed databases to identify articles posted before 27 December 2017, with no language restrictions. Data on the number, frequency, and mortality of HW infection and exposure risks were extracted.

Results

Ninety-four articles related to 22 outbreaks were included. HW infections composed 2%-100% of cases in EVD and 5%-50% of cases in MVD outbreaks. Among exposed HWs, 0.6%-92% developed EVD, and 1%-10% developed MVD. HW infection rates were consistent through outbreaks. The most common exposure risk situations were inadequate personal protective equipment and exposure to patients with unrecognized EVD/MVD. Similar risks were reported in past EVD/MVD outbreaks and in the recent outbreak in West Africa.

Conclusions

Many outbreaks reported high proportions of infected HWs. Similar HW infection rates and exposure risk factors in both past and recent EVD and MVD outbreaks emphasize the need to improve the implementation of appropriate infection control measures consistently across all healthcare settings.

Reporting quality of the 2014 Ebola outbreak in Africa: A systematic analysis

The objective of this study was to conduct a systematic analysis of the reporting quality of the Ebola Virus Disease (EVD) outbreak in West Africa from 2014-2018 using the Modified STROBE statement. We included studies on the 2014 EVD outbreak alone, limited to those on human patients in Africa. We searched the following databases (MEDLINE, EMBASE, and Web of Science) for outbreak reports published between 2014-2018. We assessed factors potentially associated with the quality of reporting. A total of 69 of 131 (53%) articles within the full-text review fulfilled our eligibility criteria and underwent the Modified STROBE assessment for analyzing the quality of reporting. The Modified STROBE scores of the included studies ranged from 11-26 points and the mean was found to be 19.54 out of 30 with a standard deviation (SD) of ± 4.30. The top three reported Modified STROBE components were descriptive characteristics of study participants, scientific background and evidence rational, and clinical significance of observations. More than 75% of the studies met a majority of the criteria in the Modified STROBE assessment tool. Information that was commonly missing included addressing potential source of bias, sensitivity analysis, further results/analysis such as risk estimates and odds ratios, presence of a flowchart, and addressing missing data. In multivariable analysis, peer-reviewed publication was the only predictor that remained significantly associated with a higher Modified STROBE score. In conclusion, the large range of Modified STROBE scores observed indicates variability in the quality of outbreak reports for EVD. The review identified strong reporting in some areas, whereas other areas are in need of improvement, in particular providing an important description of the outbreak setting and identifying any external elements (potential biases and confounding factors) that could hinder the credibility of the findings.

Health system capacity in Sydney, Australia in the event of a biological attack with smallpox

Planning for a re-emergent epidemic of smallpox requires surge capacity of space, resources and personnel within health systems. There are many uncertainties in such a scenario, including likelihood and size of an attack, speed of response and health system capacity. We used a model for smallpox transmission to determine requirements for hospital beds, contact tracing and health workers (HCWs) in Sydney, Australia, during a modelled epidemic of smallpox. Sensitivity analysis was done on attack size, speed of response and proportion of case isolation and contact tracing. We estimated 100638 clinical HCWs and 14595 public hospital beds in Sydney. Rapid response, case isolation and contact tracing are influential on epidemic size, with case isolation more influential than contact tracing. With 95% of cases isolated, outbreak control can be achieved within 100 days even with only 50% of contacts traced. However, if case isolation and contact tracing both fall to 50%, epidemic control is lost. With a smaller initial attack and a response commencing 20 days after the attack, health system impacts are modest. The requirement for hospital beds will vary from up to 4% to 100% of all available beds in best and worst case scenarios. If the response is delayed, or if the attack infects 10000 people, all available beds will be exceeded within 40 days, with corresponding surge requirements for clinical health care workers (HCWs). We estimated there are 330 public health workers in Sydney with up to 940,350 contacts to be traced. At least 3 million respirators will be needed for the first 100 days. To ensure adequate health system capacity, rapid response, high rates of case isolation, excellent contact tracing and vaccination, and protection of HCWs should be a priority. Surge capacity must be planned. Failures in any of these could cause health system failure, with inadequate beds, quarantine spaces, personnel, PPE and inability to manage other acute health conditions.

Dynamics of Ebola Disease in the Framework of Different Fractional Derivatives

In recent years the world has witnessed the arrival of deadly infectious diseases that have taken many lives across the globe. To fight back these diseases or control their spread, mankind relies on modeling and medicine to control, cure, and predict the behavior of such problems. In the case of Ebola, we observe spread that follows a fading memory process and also shows crossover behavior. Therefore, to capture this kind of spread one needs to use differential operators that posses crossover properties and fading memory. We analyze the Ebola disease model by considering three differential operators, that is the Caputo, Caputo–Fabrizio, and the Atangana–Baleanu operators. We present brief detail and some mathematical analysis for each operator applied to the Ebola model. We present a numerical approach for the solution of each operator. Further, numerical results for each operator with various values of the fractional order parameter α are presented. A comparison of the suggested operators on the Ebola disease model in the form of graphics is presented. We show that by decreasing the value of the fractional order parameter α, the number of individuals infected by Ebola decreases efficiently and conclude that for disease elimination, the Atangana–Baleanu operator is more useful than the other two.

Active Case Finding for Improved Ebola Virus Disease Case Detection in Nimba County, Liberia, 2014/2015: Lessons Learned

Objectives. Early case detection and isolation of patients infected with highly infectious diseases are crucial in the management and control of epidemics such as Ebola Virus Disease (EVD). In this paper, we share the lessons learned from implementation of active case finding as a strategy for improved EVD case detection in Nimba County, Liberia. Methods. We adopted the World Health Organization (WHO) active surveillance strategy to identify and report suspected EVD cases, follow up contacts of confirmed cases, and report community deaths. We identified, trained, and deployed 1060 Community Health Volunteers (CHVs) in 718 communities in Nimba County. The CHVs were supervised by 142 health workers within their catchment area. The health workers were supervised by the District Health Officers (DHOs). The DHOs reported to the County Health Team (CHT) who provided supportive supervision. Data collection was based on the EVD contact tracing and active case finding forms adopted from WHO. Data analysis was based on epi-weeks. Results. The number of EVD suspected cases increased by more than 75% following the initiation of active case finding. Average duration between symptom onset and case detection reduced from between three and five days to within 24 hours. Collection of oral swabs from dead bodies increased from two to 15 within the first week of active case finding strategy implementation. Reporting of other IDSR priority diseases and conditions also improved. Conclusion. Active case finding strategy in Nimba increased suspected EVD case detection and reduced the duration between onset of symptoms and detection of cases.

Mathematical modeling of contact tracing as a control strategy of Ebola virus disease

More than 20 outbreaks of Ebola virus disease have occurred in Africa since 1976, and yet no adequate treatment is available. Hence, prevention, control measures and supportive treatment remain the only means to avoid the disease. Among these measures, contact tracing occupies a prominent place. In this paper, we propose a simple mathematical model that incorporates imperfect contact tracing, quarantine and hospitalization (or isolation). The control reproduction number [Formula: see text] of each sub-model and for the full model are computed. Theoretically, we prove that when [Formula: see text] is less than one, the corresponding model has a unique globally asymptotically stable disease-free equilibrium. Conversely, when [Formula: see text] is greater than one, the disease-free equilibrium becomes unstable and a unique globally asymptotically stable endemic equilibrium arises. Furthermore, we numerically support the analytical results and assess the efficiency of different control strategies. Our main observation is that, to eradicate EVD, the combination of high contact tracing (up to 90%) and effective isolation is better than all other control measures, namely: (1) perfect contact tracing, (2) effective isolation or full hospitalization, (3) combination of medium contact tracing and medium isolation.

A qualitative inquiry on the status and adequacy of legal instruments establishing infectious disease surveillance in Nigeria

INTRODUCTION

The threat of devastating disease outbreaks is on the rise with several outbreaks recorded across the world in the last five years. The intractable Ebola Virus Disease outbreak in West Africa which spread to Nigeria was a reawakening point. This study aims to review the status and adequacy of the legal framework for disease surveillance in Nigeria. Methods: a mixed methods approach comprising of document reviews and key informant interviews was used in data collection.

METHODS

A mixed methods approach comprising of document reviews and key informant interviews was used in data collection.

RESULTS

Fourteen key informants from the federal ministry of health (FMOH) and six States were interviewed. Five legal instruments were identified and reviewed. The Quarantine Act of 1926 remains the active National Law on disease surveillance in Nigeria. An Integrated Disease Surveillance and Response Policy (IDSR) was developed in 2005 as the means for achieving the International Health Regulations (IHR). All six states claimed to have adopted the national IDSR policy though none could present a domesticated version of the policy. Key informants were concerned that Nigeria does not yet have an adequate legal framework for disease surveillance.

CONCLUSION

The legal instruments establishing disease surveillance in Nigeria require strengthening and possibly enactment as a National Law in order to address emerging disease threats.

Lack of Secondary Transmission of Ebola Virus from Healthcare Worker to 238 Contacts, United Kingdom, December 2014

In December 2014, Ebola virus disease (EVD) was diagnosed in a healthcare worker in the United Kingdom after the worker returned from an Ebola treatment center in Sierra Leone. The worker flew on 2 flights during the early stages of disease. Follow-up of 238 contacts showed no evidence of secondary transmission of Ebola virus.

Contributions of the US Centers for Disease Control and Prevention in Implementing the Global Health Security Agenda in 17 Partner Countries

The Global Health Security Agenda (GHSA), a partnership of nations, international organizations, and civil society, was launched in 2014 with a mission to build countries’ capacities to respond to infectious disease threats and to foster global compliance with the International Health Regulations (IHR 2005). The US Centers for Disease Control and Prevention (CDC) assists partner nations to improve IHR 2005 capacities and achieve GHSA targets. To assess progress through these CDC-supported efforts, we analyzed country activity reports dating from April 2015 through March 2017. Our analysis shows that CDC helped 17 Phase I countries achieve 675 major GHSA accomplishments, particularly in the cross-cutting areas of public health surveillance, laboratory systems, workforce development, and emergency response management. CDC’s engagement has been critical to these accomplishments, but sustained support is needed until countries attain IHR 2005 capacities, thereby fostering national and regional health protection and ensuring a world safer and more secure from global health threats.

Public reaction to Chikungunya outbreaks in Italy-Insights from an extensive novel data streams-based structural equation modeling analysis

The recent outbreak of Chikungunya virus in Italy represents a serious public health concern, which is attracting media coverage and generating public interest in terms of Internet searches and social media interactions. Here, we sought to assess the Chikungunya-related digital behavior and the interplay between epidemiological figures and novel data streams traffic. Reaction to the recent outbreak was analyzed in terms of Google Trends, Google News and Twitter traffic, Wikipedia visits and edits, and PubMed articles, exploiting structural modelling equations. A total of 233,678 page-views and 150 edits on the Italian Wikipedia page, 3,702 tweets, 149 scholarly articles, and 3,073 news articles were retrieved. The relationship between overall Chikungunya cases, as well as autochthonous cases, and tweets production was found to be fully mediated by Chikungunya-related web searches. However, in the allochthonous/imported cases model, tweet production was not found to be significantly mediated by epidemiological figures, with web searches still significantly mediating tweet production. Inconsistent relationships were detected in mediation models involving Wikipedia usage as a mediator variable. Similarly, the effect between news consumption and tweets production was suppressed by the Wikipedia usage. A further inconsistent mediation was found in the case of the effect between Wikipedia usage and tweets production, with web searches as a mediator variable. When adjusting for the Internet penetration index, similar findings could be obtained, with the important exception that in the adjusted model the relationship between GN and Twitter was found to be partially mediated by Wikipedia usage. Furthermore, the link between Wikipedia usage and PubMed/MEDLINE was fully mediated by GN, differently from what was found in the unadjusted model. In conclusion-a significant public reaction to the current Chikungunya outbreak was documented. Health authorities should be aware of this, recognizing the role of new technologies for collecting public concerns and replying to them, disseminating awareness and avoid misleading information.

Mathematical model of the effects of government intervention and rehabilitation of prostitution

In the United States, prostitution is considered illegal in all but one state; Nevada allows some legal activities in exchange for substantial guidelines. In 2010, approximately 43,600 females were arrested for prostitution. Numerous intervention programs were established in order to obstruct the lifestyle of a prostitute (PRP, Project ROSE, etc.). There are many documentations and programs that share their forethought on prostitution; however, few target prostitution directly. To determine the dynamics of prostitution, this paper constructs a four-class compartmental model that focuses on the effectiveness of government intervention and rehabilitation of prostitutes mathematically. The basic reproductive number, [Formula: see text], helps to discover the threshold values for the dynamics of prostitution to become both prevalent or absent in society. This paper predominately observes government intervention to curtail a prostitution prevalent society. Various parameters and variables help to define and indicate the dynamics of prostitution to construct viable simulations. Successful prostitution interaction prevention deemed essential in prostitution prevention; however, government intervention corresponding with successful rehabilitation competitively challenges prostitution interaction prevention in reducing basic reproductive values.

A Risk Analysis Approach to Prioritizing Epidemics: Ebola Virus Disease in West Africa as a Case Study

The 2014 Ebola virus disease (EVD) outbreak affected several countries worldwide, including six West African countries. It was the largest Ebola epidemic in the history and the first to affect multiple countries simultaneously. Significant national and international delay in response to the epidemic resulted in 28,652 cases and 11,325 deaths. The aim of this study was to develop a risk analysis framework to prioritize rapid response for situations of high risk. Based on findings from the literature, sociodemographic features of the affected countries, and documented epidemic data, a risk scoring framework using 18 criteria was developed. The framework includes measures of socioeconomics, health systems, geographical factors, cultural beliefs, and traditional practices. The three worst affected West African countries (Guinea, Sierra Leone, and Liberia) had the highest risk scores. The scores were much lower in developed countries that experienced Ebola compared to West African countries. A more complex risk analysis framework using 18 measures was compared with a simpler one with 10 measures, and both predicted risk equally well. A simple risk scoring system can incorporate measures of hazard and impact that may otherwise be neglected in prioritizing outbreak response. This framework can be used by public health personnel as a tool to prioritize outbreak investigation and flag outbreaks with potentially catastrophic outcomes for urgent response. Such a tool could mitigate costly delays in epidemic response.

Modeling ebola virus disease transmissions with reservoir in a complex virus life ecology

We propose a new deterministic mathematical model for the transmission dynamics of Ebola Virus Disease (EVD) in a complex Ebola virus life ecology. Our model captures as much as possible the features and patterns of the disease evolution as a three cycle transmission process in the two ways below. Firstly it involves the synergy between the epizootic phase (during which the disease circulates periodically amongst non-human primates populations and decimates them), the enzootic phase (during which the disease always remains in fruit bats population) and the epidemic phase (during which the EVD threatens and decimates human populations). Secondly it takes into account the well-known, the probable/suspected and the hypothetical transmission mechanisms (including direct and indirect routes of contamination) between and within the three different types of populations consisting of humans, animals and fruit bats. The reproduction number R0 for the full model with the environmental contamination is derived and the global asymptotic stability of the disease free equilibrium is established when R0andlt;1. It is conjectured that there exists a unique globally asymptotically stable endemic equilibrium for the full model when R0andgt;1. The role of a contaminated environment is assessed by comparing the human infected component for the sub-model without the environment with that of the full model. Similarly, the sub-model without animals on the one hand and the sub-model without bats on the other hand are studied. It is shown that bats influence more the dynamics of EVD than the animals. Global sensitivity analysis shows that the effective contact rate between humans and fruit bats and the mortality rate for bats are the most influential parameters on the latent and infected human individuals. Numerical simulations, apart from supporting the theoretical results and the existence of a unique globally asymptotically stable endemic equilibrium for the full model, suggest further that: (1) fruit bats are more important in the transmission processes and the endemicity level of EVD than animals. This is in line with biological findings which identified bats as reservoir of Ebola viruses; (2) the indirect environmental contamination is detrimental to human beings, while it is almost insignificant for the transmission in bats.

Population Genetic Structure in Glyphosate-Resistant and -Susceptible Palmer Amaranth (Amaranthus palmeri) Populations Using Genotyping-by-sequencing (GBS)

Palmer amaranth (Amaranthus palmeri) is a major weed in United States cotton and soybean production systems. Originally native to the Southwest, the species has spread throughout the country. In 2004 a population of A. palmeri was identified with resistance to glyphosate, a herbicide heavily relied on in modern no-tillage and transgenic glyphosate-resistant (GR) crop systems. This project aims to determine the degree of genetic relatedness among eight different populations of GR and glyphosate-susceptible (GS) A. palmeri from various geographic regions in the United States by analyzing patterns of phylogeography and diversity to ascertain whether resistance evolved independently or spread from outside to an Arizona locality (AZ-R). Shikimic acid accumulation and EPSPS genomic copy assays confirmed resistance or susceptibility. With a set of 1,351 single nucleotide polymorphisms (SNPs), discovered by genotyping-by-sequencing (GBS), UPGMA phylogenetic analysis, principal component analysis, Bayesian model-based clustering, and pairwise comparisons of genetic distances were conducted. A GR population from Tennessee and two GS populations from Georgia and Arizona were identified as genetically distinct while the remaining GS populations from Kansas, Arizona, and Nebraska clustered together with two GR populations from Arizona and Georgia. Within the latter group, AZ-R was most closely related to the GS populations from Kansas and Arizona followed by the GR population from Georgia. GR populations from Georgia and Tennessee were genetically distinct from each other. No isolation by distance was detected and A. palmeri was revealed to be a species with high genetic diversity. The data suggest the following two possible scenarios: either glyphosate resistance was introduced to the Arizona locality from the east, or resistance evolved independently in Arizona. Glyphosate resistance in the Georgia and Tennessee localities most likely evolved separately. Thus, modern farmers need to continue to diversify weed management practices and prevent seed dispersal to mitigate herbicide resistance evolution in A. palmeri.

Characterizing the dynamics underlying global spread of epidemics

Over the past few decades, global metapopulation epidemic simulations built with worldwide air-transportation data have been the main tool for studying how epidemics spread from the origin to other parts of the world (e.g., for pandemic influenza, SARS, and Ebola). However, it remains unclear how disease epidemiology and the air-transportation network structure determine epidemic arrivals for different populations around the globe. Here, we fill this knowledge gap by developing and validating an analytical framework that requires only basic analytics from stochastic processes. We apply this framework retrospectively to the 2009 influenza pandemic and 2014 Ebola epidemic to show that key epidemic parameters could be robustly estimated in real-time from public data on local and global spread at very low computational cost. Our framework not only elucidates the dynamics underlying global spread of epidemics but also advances our capability in nowcasting and forecasting epidemics.

The Ebola outbreak, 2013-2016: old lessons for new epidemics

Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013-2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Potential for broad-scale transmission of Ebola virus disease during the West Africa crisis: lessons for the Global Health security agenda

Background

The 2014–2016 Ebola crisis in West Africa had approximately eight times as many reported deaths as the sum of all previous Ebola outbreaks. The outbreak magnitude and occurrence of multiple Ebola cases in at least seven countries beyond Liberia, Sierra Leone, and Guinea, hinted at the possibility of broad-scale transmission of Ebola.

Main text

Using a modeling tool developed by the US Centers for Disease Control and Prevention during the Ebola outbreak, we estimated the number of Ebola cases that might have occurred had the disease spread beyond the three countries in West Africa to cities in other countries at high risk for disease transmission (based on late 2014 air travel patterns). We estimated Ebola cases in three scenarios: a delayed response, a Liberia-like response, and a fast response scenario. Based on our estimates of the number of Ebola cases that could have occurred had Ebola spread to other countries beyond the West African foci, we emphasize the need for improved levels of preparedness and response to public health threats, which is the goal of the Global Health Security Agenda. Our estimates suggest that Ebola could have potentially spread widely beyond the West Africa foci, had local and international health workers and organizations not committed to a major response effort. Our results underscore the importance of rapid detection and initiation of an effective, organized response, and the challenges faced by countries with limited public health systems. Actionable lessons for strengthening local public health systems in countries at high risk of disease transmission include increasing health personnel, bolstering primary and critical healthcare facilities, developing public health infrastructure (e.g. laboratory capacity), and improving disease surveillance. With stronger local public health systems infectious disease outbreaks would still occur, but their rapid escalation would be considerably less likely, minimizing the impact of public health threats such as Ebola.

Conclusions

The Ebola outbreak could have potentially spread to other countries, where limited public health surveillance and response capabilities may have resulted in additional foci. Health security requires robust local health systems that can rapidly detect and effectively respond to an infectious disease outbreak.

Electronic supplementary material

The online version of this article (10.1186/s40249-017-0373-4) contains supplementary material, which is available to authorized users.

Comparing "insider" and "outsider" news coverage of the 2014 Ebola outbreak

OBJECTIVES

Information provided by news media during an infectious disease outbreak can affect the actions taken to safeguard public health. There has been little evaluation of how the content of news published during an outbreak varies by location of the news outlet. This study analyzes coverage of the 2014 Ebola outbreak by one news outlet operating within a country affected by the outbreak and one country not directly affected.

METHODS

A qualitative content analysis was conducted of articles published in two national news outlets, The Globe and Mail (Canada) and the Vanguard (Nigeria), between January 1 and December 31, 2014. Articles available through LexisNexis Academic were sorted by date and sampled using a stratified sampling method (The Globe and Mail n = 100; Vanguard n = 105). A coding scheme was developed and modified to incorporate emerging themes until saturation was achieved.

RESULTS

There were substantial differences in outbreak coverage in terms of the topic and content of the articles, as well as the sources consulted. The Globe and Mail framed the outbreak in terms of national security and national interests, as well as presenting it as an international humanitarian crisis. In contrast, the Vanguard framed the outbreak almost exclusively in terms of public health.

CONCLUSION

Our findings highlight how different geographic contexts can shape reporting on the same event. Further research is required to investigate how the political, social or economic situations of a country shape its news media, potentially influencing actions taken to control disease outbreaks.

The RAPIDD Ebola forecasting challenge: Model description and synthetic data generation

The Ebola forecasting challenge organized by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Fogarty International Center relies on synthetic disease datasets generated by numerical simulations of a highly detailed spatially-structured agent-based model. We discuss here the architecture and technical steps of the challenge, leading to datasets that mimic as much as possible the data collection, reporting, and communication process experienced in the 2014-2015 West African Ebola outbreak. We provide a detailed discussion of the model's definition, the epidemiological scenarios' construction, synthetic patient database generation and the data communication platform used during the challenge. Finally we offer a number of considerations and takeaways concerning the extension and scalability of synthetic challenges to other infectious diseases.

Methods for estimating disease transmission rates: Evaluating the precision of Poisson regression and two novel methods

Precise estimates of disease transmission rates are critical for epidemiological simulation models. Most often these rates must be estimated from longitudinal field data, which are costly and time-consuming to conduct. Consequently, measures to reduce cost like increased sampling intervals or subsampling of the population are implemented. To assess the impact of such measures we implement two different SIS models to simulate disease transmission: A simple closed population model and a realistic dairy herd including population dynamics. We analyze the accuracy of different methods for estimating the transmission rate. We use data from the two simulation models and vary the sampling intervals and the size of the population sampled. We devise two new methods to determine transmission rate, and compare these to the frequently used Poisson regression method in both epidemic and endemic situations. For most tested scenarios these new methods perform similar or better than Poisson regression, especially in the case of long sampling intervals. We conclude that transmission rate estimates are easily biased, which is important to take into account when using these rates in simulation models.

An account of the Ebola virus disease outbreak in Nigeria: implications and lessons learnt

BACKGROUND

The 2014 Ebola virus disease (EVD) outbreak remains unprecedented both in the number of cases, deaths and geographic scope. The first case of EVD was confirmed in Lagos Nigeria on 23 July 2014 and spread to involve 19 laboratory-confirmed EVD cases. The EVD cases were not limited to Lagos State as Rivers State recorded 2 confirmed cases of EVD with 1 out of the 2 dying. Swift implementation of public health measures were sufficient to forestall a country -wide spread of this dreaded disease. This exploratory formative research describes the events of the Nigeria Ebola crisis in 2014.

METHODS

This research was implemented through key informant in-depth interviews involving 15 stakeholders in the EVD outbreak in Nigeria by a team of two or three interviewers. Most of the interviews were conducted face-to-face at the various offices of the respondents and others were via the telephone. The interviews which lasted an hour on average were conducted in English, digitally recorded and notes were also taken.

RESULTS

This study elucidated the public health response to the Ebola outbreak led by Lagos State Government in conjunction with the Federal Ministry of Health. The principal strategy was an incident management approach which saw them identify and successfully follow up 894 contacts. The infected EVD cases were quarantined and treated. The Nigerian private sector and international organizations made significant contributions to the control efforts. Public health enlightenment programmes using multimodal communication strategies were rapidly deployed. Water and sanitary facilities were provided in many public schools in Lagos.

CONCLUSIONS

The 2014 Ebola outbreak in Nigeria was effectively controlled using the incident management approach with massive support provided by the private sector and international community. Eight of the confirmed cases of EVD in Nigeria eventually died (case fatality rate of 42.1%) and twelve were nursed back to good health. On October 20 2014 Nigeria was declared fee of EVD by the World Health Organization. The Nigerian EVD experience provides valuable insights to guide reforms of African health systems in preparation for future infectious diseases outbreaks.

Essential information: Uncertainty and optimal control of Ebola outbreaks

Early resolution of uncertainty during an epidemic outbreak can lead to rapid and efficient decision making, provided that the uncertainty affects prioritization of actions. The wide range in caseload projections for the 2014 Ebola outbreak caused great concern and debate about the utility of models. By coding and running 37 published Ebola models with five candidate interventions, we found that, despite this large variation in caseload projection, the ranking of management options was relatively consistent. Reducing funeral transmission and reducing community transmission were generally ranked as the two best options. Value of information (VoI) analyses show that caseloads could be reduced by 11% by resolving all model-specific uncertainties, with information about model structure accounting for 82% of this reduction and uncertainty about caseload only accounting for 12%. Our study shows that the uncertainty that is of most interest epidemiologically may not be the same as the uncertainty that is most relevant for management. If the goal is to improve management outcomes, then the focus of study should be to identify and resolve those uncertainties that most hinder the choice of an optimal intervention. Our study further shows that simplifying multiple alternative models into a smaller number of relevant groups (here, with shared structure) could streamline the decision-making process and may allow for a better integration of epidemiological modeling and decision making for policy.

Epidemiology of Ebola Virus Disease in the Western Area Region of Sierra Leone, 2014-2015

Introduction

Western Area (WA) of Sierra Leone including the capital, Freetown, experienced an unprecedented outbreak of Ebola from 2014 to 2015. At the onset of the epidemic, there was little information about the epidemiology, transmission dynamics, and risk factors in urban settings as previous outbreaks were limited to rural/semi-rural settings. This study, therefore, aimed to describe the epidemiology of the outbreak and the factors which had most impact on the transmission of the epidemic and whether there were different drivers from those previously described in rural settings.

Methods

We conducted a descriptive epidemiology study in WA, Sierra Leone using secondary data from the National Ebola outbreak database. We also reviewed the Ebola situation reports, response strategy documents, and other useful documents.

Results

A total of 4,955 Ebola cases were identified between June 2014 and November 2015, although there were reports of cases occurring in WA toward end of May. All wards were affected, and Waterloo Area I (Ward 330), the capital city of Western Area Rural District, recorded the highest numbers of cases (580) and deaths (236). Majority of cases (63.4%) and deaths (66.8%) were in WA Urban District (WAU); 44 cases were imported from other provinces. Only 20% of cases had a history of contact with an Ebola case, and more than 30% were death alerts. Equal numbers of males and females were infected, and very few cases (3.2%) were health workers. Overall, transmission was through contact with infected individuals, and intense transmission occurred at the community level. In WAU, transmission was mostly between neighbors and among inhabitants of shared accommodations. The drivers of transmission included high population movement to and from WA, overcrowding, fear and lack of trust in the response, and negative community behaviors. Transmission was mostly through contact and with limited transmission through sex and breast milk.

Conclusion

The unprecedented outbreak in WA was attributed to delayed detection, inadequate preparedness and response, intense population movements, overcrowding, and unresponsive communities. Anticipation, strengthening preparedness for early detection, and swift and effective response remains critical in mitigating a potential urban explosion of similar future outbreaks.

Perspectives on model forecasts of the 2014-2015 Ebola epidemic in West Africa: lessons and the way forward

The unprecedented impact and modeling efforts associated with the 2014-2015 Ebola epidemic in West Africa provides a unique opportunity to document the performances and caveats of forecasting approaches used in near-real time for generating evidence and to guide policy. A number of international academic groups have developed and parameterized mathematical models of disease spread to forecast the trajectory of the outbreak. These modeling efforts often relied on limited epidemiological data to derive key transmission and severity parameters, which are needed to calibrate mechanistic models. Here, we provide a perspective on some of the challenges and lessons drawn from these efforts, focusing on (1) data availability and accuracy of early forecasts; (2) the ability of different models to capture the profile of early growth dynamics in local outbreaks and the importance of reactive behavior changes and case clustering; (3) challenges in forecasting the long-term epidemic impact very early in the outbreak; and (4) ways to move forward. We conclude that rapid availability of aggregated population-level data and detailed information on a subset of transmission chains is crucial to characterize transmission patterns, while ensemble-forecasting approaches could limit the uncertainty of any individual model. We believe that coordinated forecasting efforts, combined with rapid dissemination of disease predictions and underlying epidemiological data in shared online platforms, will be critical in optimizing the response to current and future infectious disease emergencies.

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.

Toward a Realistic Modeling of Epidemic Spreading with Activity Driven Networks

Models of epidemic spreading are widely used to predict the evolution of an outbreak, test specific intervention scenarios, and steer interventions in the field. Compartmental models are the most common class of models. They are very effective for qualitative analysis, but they rely on simplifying assumptions, such as homogeneous mixing and time scale separation. On the other end of the spectrum, detailed agent-based models, based on realistic mobility pattern models, provide extremely accurate predictions. However, these models require significant computing power and are not suitable for analytical treatment. Our research aims at bridging the gap between these two approaches, toward time-varying network models that are sufficiently accurate to make predictions for real-world applications, while being computationally affordable and amenable to analytical treatment. We leverage the novel paradigm of activity driven networks (ADNs), a particular type of time-varying network that accounts for inherent inhomogeinities within a population. Starting from the basic incarnation of ADNs, we expand on the framework to include behavioral factors triggered by health status and spreading awareness. The enriched paradigm is then utilized to model the 2014–2015 Ebola Virus Disease (EVD) spreading in Liberia, and perform a what-if analysis on the timely application of sanitary interventions in the field. Finally, we propose a new formulation, which is amenable to analytical treatment, beyond the mere computation of the epidemic threshold.