Outbreak of Ebola virus disease in the Democratic Republic of the Congo, April-May, 2018: an epidemiological study

Ebola virus disease mathematical models and epidemiological parameters: a systematic review

Ebola virus disease poses a recurring risk to human health. We conducted a systematic review (PROSPERO CRD42023393345) of Ebola virus disease transmission models and parameters published from database inception to July 7, 2023, from PubMed and Web of Science. Two people screened each abstract and full text. Papers were extracted with a bespoke Access database, 10% were double extracted. We extracted 1280 parameters and 295 models from 522 papers. Basic reproduction number estimates were highly variable, as were effective reproduction numbers, likely reflecting spatiotemporal variability in interventions. Random-effect estimates were 15·4 days (95% CI 13·2-17·5) for the serial interval, 8·5 days (7·7-9·2) for the incubation period, 9·3 days (8·5-10·1) for the symptom-onset-to-death delay, and 13·0 days (10·4-15·7) for symptom-onset-to-recovery. Common effect estimates were similar, albeit with narrower CIs. Case-fatality ratio estimates were generally high but highly variable, which could reflect heterogeneity in underlying risk factors. Although a substantial body of literature exists on Ebola virus disease models and epidemiological parameter estimates, many of these studies focus on the west African Ebola epidemic and are primarily associated with Zaire Ebola virus, which leaves a key gap in our knowledge regarding other Ebola virus species and outbreak contexts.

SIR… or MADAM? The impact of privilege on careers in epidemic modelling

As we emerge from what may be the largest global public health crises of our lives, our community of epidemic modellers is naturally reflecting. What role can modelling play in supporting decision making during epidemics? How could we more effectively interact with policy makers? How should we design future disease surveillance systems? All crucial questions. But who is going to be addressing them in 10 years' time? With high burnout and poor attrition rates in academia, both magnified in our field by our unprecedented efforts during the pandemic, and with low wages coinciding with inflation at its highest for decades, how do we retain talent? This is a multifaceted challenge, that I argue is underpinned by privilege. In this perspective, I introduce the notion of privilege and highlight how various aspects of privilege (namely gender, ethnicity, sexual orientation, language and caring responsibilities) may affect the ability of individuals to access to and progress within academic modelling careers. I propose actions that members of the epidemic modelling research community may take to mitigate these issues and ensure we have a more diverse and equitable workforce going forward.

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.

Impact of Ebola epidemics on the daily operation of existing systems in Eastern Democratic Republic of the Congo: a brief review

AIMS

to provide insights into the recent Ebola virus disease (EVD) outbreaks on different aspects of daily life in the Democratic Republic of the Congo and propose possible solutions.

METHODS

We collected information regarding the effects of EVD outbreaks on existing systems in the eastern part of the Democratic Republic of the Congo (DRC). We searched the PubMed database using the terms "impact effect Ebola outbreak system", "Management Ebola Poor Resources Settings", "Health Economic Challenges Ebola" and "Economic impact Ebola systems." Only studies focusing on epidemiology, diagnostics, sequencing, vaccination, therapeutics, ecology, work force, governance, healthcare provision and health system, and social, political, and economic aspects were considered. The search included the electronic archives of EVD outbreak reports from government and partners.

RESULTS

EVD outbreaks negatively impacts the functions of countries. The disruption in activities is proportional to the magnitude of the epidemic and slows down the transport of goods, decreases the region's tourist appeal, and increases 'brain drain'. Most low- and medium-income countries, such as the DRC, do not have a long-term holistic emergency plan for unexpected situations or sufficient resources to adequately implement countermeasures against EVD outbreaks. Although the DRC has acquired sufficient expertise in diagnostics, genomic sequencing, administration of vaccines and therapeutics, clinical trials, and research activities, deployment, operation, and maintenance of these expertise and associated tools remains a concern.

LIMITATIONS

Despite the data search extension, additional reports addressing issues related to social aspects of EVD outbreaks in DRC were not retrieved.

CONCLUSION

National leadership has not yet taken the lead in strategic, operational, or financial aspects. Therefore, national leaders should double their efforts and awareness to encourage local fundraising, sufficient budget al.location, infrastructure construction, equipment provision, and staff training, to effectively support a holistic approach in response to outbreaks, providing effective results, and all types of research activities.

Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

Performance of French medico-administrative databases in epidemiology of infectious diseases: a scoping review

The development of medico-administrative databases over the last few decades has led to an evolution and to a significant production of epidemiological studies on infectious diseases based on retrospective medical data and consumption of care. This new form of epidemiological research faces numerous methodological challenges, among which the assessment of the validity of targeting algorithm. We conducted a scoping review of studies that undertook an estimation of the completeness and validity of French medico-administrative databases for infectious disease epidemiological research. Nineteen validation studies and nine capture-recapture studies were identified. These studies covered 20 infectious diseases and were mostly based on the evaluation of hospital claimed data. The evaluation of their methodological qualities highlighted the difficulties associated with these types of research, particularly those linked to the assessment of their underlying hypotheses. We recall several recommendations relating to the problems addressed, which should contribute to the quality of future evaluation studies based on medico-administrative data and consequently to the quality of the epidemiological indicators produced from these information systems.

Data flows during public health emergencies in LMICs: A people-centered mapping of data flows during the 2018 ebola epidemic in Equateur, DRC

In infectious outbreaks, rapid case detection and reporting, coordination, and context-specific strategies are needed for rapid containment. Data sharing between actors, and the speed and content of data flows, is essential for expediting epidemic response. In this study, researchers mapped data flows during the 2018 Ebola Virus Disease (EVD) outbreak in Equateur Province in the Democratic Republic of the Congo using semi-structured interviews, ethnographic research, and focus groups with EVD response actors. During this research, we mapped and tracked data collection, transmission, storage, sharing, and use patterns. Target participants included: key organizational actors in the EVD outbreaks responses, including local (primary health, community-based, hospital), provincial (MoPH, DRC Red Cross), and international (WHO, UN organizations, international first-responders) stakeholders. We found that a community-based surveillance system enabled the rapid detection of a hemorrhagic fever outbreak, resulting in the rapid laboratory confirmation of EVD. With the arrival of international organizations to provide support to the EVD response, routine surveillance systems continued to function robustly. However, the establishment of a vertical EVD response architecture created challenges for the response. Data flows during the Equateur outbreak were hampered by numerous challenges in the domains of early warning, line lists of cases, and contact tracing, which impeded surveillance and data flows. We therefore argue that structuring health information systems for preparedness requires taking a person-centered approach to data production, flow, and analysis.

Emerging challenges to prisoners vaccination of covid-19: Historical, legal and humanitarian view

This research aims to present a legal history of the prisoners’ treatment in global crises along with presenting an overview of prisoners’ treatment during Covid-19 in view of International Humanitarian Laws. Using the formative research method with a conceptual approach and statute approach, data was gathered from various legal documents related to prisoners’ health laws linked to legal purpose theories. This study further explains the need to treat old age prisoners on a priority basis and to what extent international health organizations are making efforts to establish criteria to vaccinate this societal segment. The international regulatory framework was deeply analyzed to draw conclusions and recommendations along with WHO efforts. It was revealed that there exist adequate laws regarding priority health treatment of the prisoners in crises times but existed an enormous need to highlight and address the sensitive humanitarian issue. Additionally, WHO and other international organizations have also revised the international laws during Covid-19 to treat the prisoners. However, there is an immense need to devise explicit regulations regarding the accessibility of the vaccine to all the groups of society, including prisoners. The provision of a detailed overview of international laws and treaties regarding prisoners’ priority health treatment is a major advance of this research. Further recommendations for the developed and developing nations and future research directions are suggested.

Modeling a sustainable vaccine supply chain for a healthcare system

This study develops a vaccine supply chain (VSC) to ensure sustainable distribution during a global crisis in a developing economy. In this study, a multi-objective mixed-integer programming (MIP) model is formulated to develop the VSC, ensuring the entire network's economic performance. This is achieved by minimizing the overall cost of vaccine distribution and ensuring environmental and social sustainability by minimizing greenhouse gas (GHG) emissions and maximizing job opportunities in the entire network. The shelf-life of vaccines and the uncertainty associated with demand and supply chain (SC) parameters are also considered in this study to ensure the robustness of the model. To solve the model, two recently developed metaheuristics-namely, the multi-objective social engineering optimizer (MOSEO) and multi-objective feasibility enhanced particle swarm optimization (MOFEPSO) methods-are used, and their results are compared. Further, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model has been integrated into the optimization model to determine the best solution from a set of non-dominated solutions (NDSs) that prioritize environmental sustainability. The results are analyzed in the context of the Bangladeshi coronavirus disease (COVID-19) vaccine distribution systems. Numerical illustrations reveal that the MOSEO-TOPSIS model performs substantially better in designing the network than the MOFEPSO-TOPSIS model. Furthermore, the solution from MOSEO results in achieving better environmental sustainability than MOFEPSO with the same resources. Results also reflect that the proposed MOSEO-TOPSIS can help policymakers establish a VSC during a global crisis with enhanced economic, environmental, and social sustainability within the healthcare system.

Design, Implementation, and Outcomes of a Volunteer-Staffed Case Investigation and Contact Tracing Initiative at an Urban Academic Medical Center

IMPORTANCE

The COVID-19 pandemic has claimed nearly 6 million lives globally as of February 2022. While pandemic control efforts, including contact tracing, have traditionally been the purview of state and local health departments, the COVID-19 pandemic outpaced health department capacity, necessitating actions by private health systems to investigate and control outbreaks, mitigate transmission, and support patients and communities.

OBJECTIVE

To investigate the process of designing and implementing a volunteer-staffed contact tracing program at a large academic health system from April 2020 to May 2021, including program structure, lessons learned through implementation, results of case investigation and contact tracing efforts, and reflections on how constrained resources may be best allocated in the current pandemic or future public health emergencies.

DESIGN, SETTING, AND PARTICIPANTS

This case series study was conducted among patients at the University of Pennsylvania Health System and in partnership with the Philadelphia Department of Public Health. Patients who tested positive for COVID-19 were contacted to counsel them regarding safe isolation practices, identify and support quarantine of their close contacts, and provide resources, such as food and medicine, needed during isolation or quarantine.

RESULTS

Of 5470 individuals who tested positive for COVID-19 and received calls from a volunteer, 2982 individuals (54.5%; median [range] age, 42 [18-97] years; 1628 [59.4%] women among 2741 cases with sex data) were interviewed; among 2683 cases with race data, there were 110 Asian individuals (3.9%), 1476 Black individuals (52.7%), and 817 White individuals (29.2%), and among 2667 cases with ethnicity data, there were 366 Hispanic individuals (13.1%) and 2301 individuals who were not Hispanic (82.6%). Most individuals lived in a household with 2 to 5 people (2125 of 2904 individuals with household data [71.6%]). Of 3222 unique contacts, 1780 close contacts (55.2%; median [range] age, 40 [18-97] years; 866 [55.3%] women among 1565 contacts with sex data) were interviewed; among 1523 contacts with race data, there were 69 Asian individuals (4.2%), 705 Black individuals (43.2%), and 573 White individuals (35.1%), and among 1514 contacts with ethnicity data, there were 202 Hispanic individuals (12.8%) and 1312 individuals (83.4%) who were not Hispanic. Most contacts lived in a household with 2 to 5 people (1123 of 1418 individuals with household data [79.2%]). Of 3324 cases and contacts who completed a questionnaire on unmet social needs, 907 (27.3%) experienced material hardships that would make it difficult for them to isolate or quarantine safely. Such hardship was significantly less common among White compared with Black participants (odds ratio, 0.20; 95% CI, 0.16-0.25).

CONCLUSIONS AND RELEVANCE

These findings demonstrate the feasibility and challenges of implementing a case investigation and contact tracing program at an academic health system. In addition to successfully engaging most assigned COVID-19 cases and close contacts, contact tracers shared health information and material resources to support isolation and quarantine, thus filling local public health system gaps and supporting local pandemic control.

Zaire ebolavirus surveillance near the Bikoro region of the Democratic Republic of the Congo during the 2018 outbreak reveals presence of seropositive bats

On the 8th of May, 2018, an outbreak of Ebola virus disease (EVD) was declared, originating in the Bikoro region of the Democratic Republic of the Congo (DRC) near the border with neighboring Republic of the Congo (ROC). Frequent trade and migration occur between DRC and ROC-based communities residing along the Congo River. In June 2018, a field team was deployed to determine whether Zaire ebolavirus (Ebola virus (EBOV)) was contemporaneously circulating in local bats at the human-animal interface in ROC near the Bikoro EVD outbreak. Samples were collected from bats in the Cuvette and Likouala departments, ROC, bordering the Équateur Province in DRC where the Bikoro EVD outbreak was first detected. EBOV genomic material was not detected in bat-derived samples by targeted quantitative reverse transcription-polymerase chain reaction or by family-level consensus polymerase chain reaction; however, serological data suggests recent exposure to EBOV in bats in the region. We collected serum from 144 bats in the Cuvette department with 6.9% seropositivity against the EBOV glycoprotein and 14.3% seropositivity for serum collected from 27 fruit bats and one Molossinae in the Likouala department. We conclude that proactive investment in longitudinal sampling for filoviruses at the human-animal interface, coupled with ecological investigations are needed to identify EBOV wildlife reservoirs.

Real-time estimation of the epidemic reproduction number: Scoping review of the applications and challenges

The time-varying reproduction number (Rt) is an important measure of transmissibility during outbreaks. Estimating whether and how rapidly an outbreak is growing (Rt > 1) or declining (Rt < 1) can inform the design, monitoring and adjustment of control measures in real-time. We use a popular R package for Rt estimation, EpiEstim, as a case study to evaluate the contexts in which Rt estimation methods have been used and identify unmet needs which would enable broader applicability of these methods in real-time. A scoping review, complemented by a small EpiEstim user survey, highlight issues with the current approaches, including the quality of input incidence data, the inability to account for geographical factors, and other methodological issues. We summarise the methods and software developed to tackle the problems identified, but conclude that significant gaps remain which should be addressed to enable easier, more robust and applicable estimation of Rt during epidemics.

COVID-19 in Japan, January-March 2020: insights from the first three months of the epidemic

BACKGROUND

Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data.

METHODS

We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs.

RESULTS

The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16-23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms.

CONCLUSIONS

Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.

Measuring the unknown: An estimator and simulation study for assessing case reporting during epidemics

The fraction of cases reported, known as 'reporting', is a key performance indicator in an outbreak response, and an essential factor to consider when modelling epidemics and assessing their impact on populations. Unfortunately, its estimation is inherently difficult, as it relates to the part of an epidemic which is, by definition, not observed. We introduce a simple statistical method for estimating reporting, initially developed for the response to Ebola in Eastern Democratic Republic of the Congo (DRC), 2018-2020. This approach uses transmission chain data typically gathered through case investigation and contact tracing, and uses the proportion of investigated cases with a known, reported infector as a proxy for reporting. Using simulated epidemics, we study how this method performs for different outbreak sizes and reporting levels. Results suggest that our method has low bias, reasonable precision, and despite sub-optimal coverage, usually provides estimates within close range (5-10%) of the true value. Being fast and simple, this method could be useful for estimating reporting in real-time in settings where person-to-person transmission is the main driver of the epidemic, and where case investigation is routinely performed as part of surveillance and contact tracing activities.

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020

Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018–2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic.

Safety and immunogenicity of 2-dose heterologous Ad26.ZEBOV, MVA-BN-Filo Ebola vaccination in healthy and HIV-infected adults: A randomised, placebo-controlled Phase II clinical trial in Africa

BACKGROUND

We investigated safety, tolerability, and immunogenicity of the heterologous 2-dose Ebola vaccination regimen in healthy and HIV-infected adults with different intervals between Ebola vaccinations.

METHODS AND FINDINGS

In this randomised, observer-blind, placebo-controlled Phase II trial, 668 healthy 18- to 70-year-olds and 142 HIV-infected 18- to 50-year-olds were enrolled from 1 site in Kenya and 2 sites each in Burkina Faso, Cote d'Ivoire, and Uganda. Participants received intramuscular Ad26.ZEBOV followed by MVA-BN-Filo at 28-, 56-, or 84-day intervals, or saline. Females represented 31.4% of the healthy adult cohort in contrast to 69.7% of the HIV-infected cohort. A subset of healthy adults received booster vaccination with Ad26.ZEBOV or saline at Day 365. Following vaccinations, adverse events (AEs) were collected until 42 days post last vaccination and serious AEs (SAEs) were recorded from signing of the ICF until the end of the study. The primary endpoint was safety, and the secondary endpoint was immunogenicity. Anti-Ebola virus glycoprotein (EBOV GP) binding and neutralising antibodies were measured at baseline and at predefined time points throughout the study. The first participant was enrolled on 9 November 2015, and the date of last participant's last visit was 12 February 2019. No vaccine-related SAEs and mainly mild-to-moderate AEs were observed among the participants. The most frequent solicited AEs were injection-site pain (local), and fatigue, headache, and myalgia (systemic), respectively. Twenty-one days post-MVA-BN-Filo vaccination, geometric mean concentrations (GMCs) with 95% confidence intervals (CIs) of EBOV GP binding antibodies in healthy adults in 28-, 56-, and 84-day interval groups were 3,085 EU/mL (2,648 to 3,594), 7,518 EU/mL (6,468 to 8,740), and 7,300 EU/mL (5,116 to 10,417), respectively. In HIV-infected adults in 28- and 56-day interval groups, GMCs were 4,207 EU/mL (3,233 to 5,474) and 5,283 EU/mL (4,094 to 6,817), respectively. Antibody responses were observed until Day 365. Ad26.ZEBOV booster vaccination after 1 year induced an anamnestic response. Study limitations include that some healthy adult participants either did not receive dose 2 or received dose 2 outside of their protocol-defined interval and that the follow-up period was limited to 365 days for most participants.

CONCLUSIONS

Ad26.ZEBOV, MVA-BN-Filo vaccination was well tolerated and immunogenic in healthy and HIV-infected African adults. Increasing the interval between vaccinations from 28 to 56 days improved the magnitude of humoral immune responses. Antibody levels persisted to at least 1 year, and Ad26.ZEBOV booster vaccination demonstrated the presence of vaccination-induced immune memory. These data supported the approval by the European Union for prophylaxis against EBOV disease in adults and children ≥1 year of age.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02564523.

Development and implementation of the Ebola Exposure Window Calculator: A tool for Ebola virus disease outbreak field investigations

During an Ebola virus disease (EVD) outbreak, calculating the exposure window of a confirmed case can assist field investigators in identifying the source of infection and establishing chains of transmission. However, field investigators often have difficulty calculating this window. We developed a bilingual (English/French), smartphone-based field application to assist field investigators in determining the exposure window of an EVD case. The calculator only requires the reported date of symptoms onset and the type of symptoms present at onset or the date of death. Prior to the release of this application, there was no similar electronic capability to enable consistent calculation of EVD exposure windows for field investigators. The Democratic Republic of the Congo Ministry of Health endorsed the application and incorporated it into trainings for field staff. Available for Apple and Android devices, the calculator continues to be downloaded even as the eastern DRC outbreak resolved. We rapidly developed and implemented a smartphone application to estimate the exposure window for EVD cases in an outbreak setting

Africa and the Nexus of poverty, malnutrition and diseases

This review examines the nexus of poverty, malnutrition and diseases in Africa, the challenges, implications and their mitigation. The paper takes a critical look at available literatures on the primary causes, modes, implications and solutions to the problems of poverty, malnutrition and diseases in Africa continent. Poverty and malnutrition are outcomes of uncontrolled rapid population growth, inefficient agricultural and industrial practices, high debt profile of many African countries due to poor governance and corruption, diseases such as AIDS epidemic, malaria, Ebola virus and COVID-19 pandemic, poor and inadequate health infrastructure and armed conflicts. African poverty scenario entails non-availability of basic human needs which makes many Africans to be very poor. Despite abundance of natural resources, the gross domestic product per capita of many African countries is among the lowest of list of nations of the world. According United Nation in 2009, 22 of 24 nations among the "Low Human Development" nations of the world on the UN's Human Development Index were found in sub-Saharan Africa. Out of the 50 countries on the United Nation list of least developed countries, 34 of them were in Africa. According to FAO data over 200 million people in sub-Saharan Africa were undernourished in 2014-2016. The prevalence of undernourishment in sub-Saharan Africa rose from 181 million in 2010 to 222 million in 2016. In 2016, Africa had the highest prevalence of undernourishment in the world and estimated to be 20% of the population. While this was alarming in Eastern Africa where one-third of the population is suspected to be undernourished. In a similar data, World Bank also found that sub-Saharan Africa Poverty and Equity Data was 47% with over 500 million people in abject poverty in 2012. Poverty is the major cause of hunger and malnutrition in Africa while hunger and malnutrition escalated the problem of diseases in African continent. Poverty has continued to torment Africa as a result of poor and harmful economic policies, conflict and war, environmental factors like drought and climate change and population growth, poor leadership and greed. With the advent of COVID-19, the problem of poverty, malnutrition and diseases has been escalated and in many African countries people find it difficult to make ends meet.

Impact of a free care policy on the utilisation of health services during an Ebola outbreak in the Democratic Republic of Congo: an interrupted time-series analysis

Background

During past outbreaks of Ebola virus disease (EVD) and other infectious diseases, health service utilisation declined among the general public, delaying health seeking behaviour and affecting population health. From May to July 2018, the Democratic Republic of Congo experienced an outbreak of EVD in Equateur province. The Ministry of Public Health introduced a free care policy (FCP) in both affected and neighbouring health zones. We evaluated the impact of this policy on health service utilisation.

Methods

Using monthly data from the national Health Management Information System from January 2017 to January 2019, we examined rates of the use of nine health services at primary health facilities: total visits; first and fourth antenatal care visits; institutional deliveries; postnatal care visits; diphtheria, pertussis and tetanus (DTP) vaccinations and visits for uncomplicated malaria, pneumonia and diarrhoea. We used controlled interrupted time series analysis with a mixed effects model to estimate changes in the rates of services use during the policy (June–September 2018) and afterwards.

Findings

Overall, use of most services increased compared to control health zones, including EVD affected areas. Total visits and visits for pneumonia and diarrhoea initially increased more than two-fold relative to the control areas (p<0.001), while institutional deliveries and first antenatal care increased between 20% and 50% (p<0.01). Visits for DTP, fourth antenatal care visits and postnatal care visits were not significantly affected. During the FCP period, visit rates followed a downward trend. Most increases did not persist after the policy ended.

Interpretation

The FCP was effective at rapidly increasing the use of some health services both EVD affected and not affected health zones, but this effect was not sustained post FCP. Such policies may mitigate the adverse impact of infectious disease outbreaks on population health.

Immunotherapeutic strategies to target vulnerabilities in the Ebolavirus glycoprotein

The 2014 Ebola virus disease (EVD) outbreak in West Africa and the subsequent outbreaks of 2018-2020 in Equator and North Kivu provinces of the Democratic Republic of the Congo illustrate the public health challenges of emerging and reemerging viruses. EVD has a high case fatality rate with a rapidly progressing syndrome of fever, rash, vomiting, diarrhea, and bleeding diathesis. Recently, two monoclonal-antibody-based therapies received United States Food and Drug Administration (FDA) approval, and there are several other passive immunotherapies that hold promise as therapeutics against other species of Ebolavirus. Here, we review concepts needed to understand mechanisms of action, present an expanded schema to define additional sites of vulnerability on the viral glycoprotein, and review current antibody-based therapeutics. The concepts described are used to gain insights into the key characteristics that represent functional targets for immunotherapies against Zaire Ebolavirus and other emerging viruses within the Ebolavirus genus.

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.

The value of infectious disease modeling and trend assessment: a public health perspective

INTRODUCTION

Disease outbreaks of acquired immunodeficiency syndrome, severe acute respiratory syndrome, pandemic H1N1, H7N9, H5N1, Ebola, Zika, Middle East respiratory syndrome, and recently COVID-19 have raised the attention of the public over the past half-century. Revealing the characteristics and epidemic trends are important parts of disease control. The biological scenarios including transmission characteristics can be constructed and translated into mathematical models, which can help to predict and gain a deeper understanding of diseases.

AREAS COVERED

This review discusses the models for infectious diseases and highlights their values in the field of public health. This information will be of interest to mathematicians and clinicians, and make a significant contribution toward the development of more specific and effective models. Literature searches were performed using the online database of PubMed (inception to August 2020).

EXPERT OPINION

Modeling could contribute to infectious disease control by means of predicting the scales of disease epidemics, indicating the characteristics of disease transmission, evaluating the effectiveness of interventions or policies, and warning or forecasting during the pre-outbreak of diseases. With the development of theories and the ability of calculations, infectious disease modeling would play a much more important role in disease prevention and control of public health.

The prevalence of PTSS under the influence of public health emergencies in last two decades: A systematic review and meta-analysis

BACKGROUND

Since the beginning of 21st century, several major public health emergencies (PHEs) have threatened the health of people globally. Posttraumatic stress symptoms (PTSS) was one of the most concerned mental health problems. The objective of this study is to systematically estimate the prevalence of PTSS under the influence of PHEs.

METHOD

We searched both English and Chinese databases. This meta-analysis used a random-effects model to estimate the prevalence of PTSS. Subgroup analyses were conducted to analyze the source of heterogeneity. Meta-regression model was used to calculate the proportion of the variance explained by subgroup moderators.

RESULTS

Forty eligible studies (n = 15,538) were identified. The results revealed a pooled prevalence of PTSS of 17.0% (95%CI: 13.5%-21.2%), higher than that of previous epidemiological survey, with high between-studies heterogeneity (Q = 1199, I2 = 96.75%, p < .001). There was variance of prevalence in different countries (4.0%-36.5%) and epidemics (12.1%-36.5%). The prevalence of PTSS showed the feature of fluctuation in the change of time (Q = 6.173, p = .290). Patients had higher prevalence (26.2%) compared to healthcare workers (HCWs) (18.5%) and community samples (12.4%) and frontline HCWs had marginally significantly higher estimated rate than general HCWs (22.2%, 95%CI:16.0%-30.1% vs. 10.4%, 95%CI: 6.4%-16.6%). The variance of prevalence screened by interview and self-reported was significant (Q = 3.393, p = .05) and studies with higher quality possessed lower prevalence (high:12.4%; moderate: 17.3%; low: 18.0%). The total variance explained by subgroup moderators was estimated 64% by meta regression model.

LIMITATIONS

Limitations include high level of heterogeneity between studies and within subgroups as well as the lack of studies with high quality and using probability sampling.

CONCLUSIONS

This study suggested that the PTSS was common under the influence of PHEs. It was crucial to further explore the psychological mechanism and effective strategies for prevention and intervention in future research with more high-quality studies.

Review of Ebola virus disease in children - how far have we come?

Ebola virus (EBOV) causes an extremely contagious viral haemorrhagic fever associated with high mortality. While, historically, children have represented a small number of total cases of Ebolavirus disease (EVD), in recent outbreaks up to a quarter of cases have been in children. They pose unique challenges in clinical management and infection prevention and control. In this review of paediatric EVD, the epidemiology of past EVD outbreaks with specific focus on children is discussed, the clinical manifestations and laboratory findings are described and key developments in clinical management including specific topics such as viral persistence and breastfeeding while considering unique psychosocial and anthropological considerations for paediatric care including of survivors and orphans and the stigma they face are discussed. In addition to summarising the literature, perspectives based on the authors' experience of EVD outbreaks in the Democratic Republic of the Congo (DRC) are described.Abbreviations: ARDS: acute respiratory distress syndrome; aOR: adjusted odds ratio; ALT: alanine transferase; ALIMA: Alliance for International Medical Action; AST: aspartate transaminase; BUN: blood urea nitrogen; CNS: central nervous system; CUBE: chambre d'urgence biosécurisée pour épidémie; COVID-19: coronavirus disease 2019; C_t: cycle threshold; DRC: Democratic Republic of Congo; ETC: ebola treatment centre; ETU: ebola treatment unit; EBOV: ebola virus; EVD: ebolavirus disease; FEAST: fluid expansion as supportive therapy; GP: glycoprotein; IV: intravenous; MEURI: monitored emergency use of unregistered interventions; NETEC: National Ebola Training and Education Centre; NP: nucleoprotein; ORS: oral rehydration solution; PALM: Pamoja Tulinde Maisha; PREVAIL: Partnership for Research on Ebola Virus in Liberia; PPE: personal protective equipment; PCR: polymerase chain reaction; PEP: post-exposure prophylaxis; RDTs: rapid diagnostic tests; RT: reverse transcriptase; RNA: ribonucleic acid; UNICEF: United Nations International Children's Emergency Fund; USA: United States of America; WHO: World Health Organization.

Microfluidic devices for the detection of viruses: aspects of emergency fabrication during the COVID-19 pandemic and other outbreaks

Extensive testing of populations against COVID-19 has been suggested as a game-changer quest to control the spread of this contagious disease and to avoid further disruption in our social, healthcare and economical systems. Nonetheless, testing millions of people for a new virus brings about quite a few challenges. The development of effective tests for the new coronavirus has become a worldwide task that relies on recent discoveries and lessons learned from past outbreaks. In this work, we review the most recent publications on microfluidics devices for the detection of viruses. The topics of discussion include different detection approaches, methods of signalling and fabrication techniques. Besides the miniaturization of traditional benchtop detection assays, approaches such as electrochemical analyses, field-effect transistors and resistive pulse sensors are considered. For emergency fabrication of quick test kits, the local capabilities must be evaluated, and the joint work of universities, industries, and governments seems to be an unequivocal necessity.

Development of an Enzyme-Linked Immunosorbent Assay to Determine the Expression Dynamics of Ebola Virus Soluble Glycoprotein during Infection

Ebola virus (EBOV) is a highly pathogenic virus with human case fatality rates of up to 90%. EBOV uses transcriptional editing to express three different glycoproteins (GPs) from its GP gene: soluble GP (sGP), GP, and small sGP (ssGP). The molecular ratio of unedited to edited mRNA is about 70% (sGP): 25% (GP): 5% (ssGP), indicating that sGP is produced more abundantly than GP. While the presence of sGP has been confirmed in the blood during human EBOV infection, there is no report about its expression dynamics. In this study, we developed an EBOV-sGP-specific sandwich enzyme-linked immunosorbent assay (ELISA) using two different available antibodies and tested several animal serum samples to determine the concentration of sGP. EBOV-sGP was detected in nonhuman primate serum samples as early as 4 days after EBOV infection, correlating with RT-qPCR positivity. This ELISA might be further developed into a diagnostic tool for detection of EBOV in patients. Furthermore, this study provides insights into the expression dynamics of sGP during infection, which are important to decipher the function that sGP plays during infection.

Photocatalytic Nanowires-Based Air Filter: Towards Reusable Protective Masks

In the last couple decades, several viral outbreaks resulting in epidemics and pandemics with thousands of human causalities have been witnessed. The current Covid-19 outbreak represents an unprecedented crisis. In stopping the virus' spread, it is fundamental to have personal protective equipment and disinfected surfaces. Here, the development of a TiO2 nanowires (TiO2NWs) based filter is reported, which it is believed will work extremely well for personal protective equipment (PPE), as well as for a new generation of air conditioners and air purifiers. Its efficiency relies on the photocatalytic generation of high levels of reactive oxygen species (ROS) upon UV illumination, and on a particularly high dielectric constant of TiO2, which is of paramount importance for enhanced wettability by the water droplets carrying the germs. The filter pore sizes can be tuned by processing TiO2NWs into filter paper. The kilogram-scale production capability of TiO2NWs gives credibility to its massive application potentials.

Strong spatial embedding of social networks generates nonstandard epidemic dynamics independent of degree distribution and clustering

Some directly transmitted human pathogens, such as influenza and measles, generate sustained exponential growth in incidence and have a high peak incidence consistent with the rapid depletion of susceptible individuals. Many do not. While a prolonged exponential phase typically arises in traditional disease-dynamic models, current quantitative descriptions of nonstandard epidemic profiles are either abstract, phenomenological, or rely on highly skewed offspring distributions in network models. Here, we create large socio-spatial networks to represent contact behavior using human population-density data, a previously developed fitting algorithm, and gravity-like mobility kernels. We define a basic reproductive number [Formula: see text] for this system, analogous to that used for compartmental models. Controlling for [Formula: see text], we then explore networks with a household-workplace structure in which between-household contacts can be formed with varying degrees of spatial correlation, determined by a single parameter from the gravity-like kernel. By varying this single parameter and simulating epidemic spread, we are able to identify how more frequent local movement can lead to strong spatial correlation and, thus, induce subexponential outbreak dynamics with lower, later epidemic peaks. Also, the ratio of peak height to final size was much smaller when movement was highly spatially correlated. We investigate the topological properties of our networks via a generalized clustering coefficient that extends beyond immediate neighborhoods, identifying very strong correlations between fourth-order clustering and nonstandard epidemic dynamics. Our results motivate the observation of both incidence and socio-spatial human behavior during epidemics that exhibit nonstandard incidence patterns.

The cost of insecurity: from flare-up to control of a major Ebola virus disease hotspot during the outbreak in the Democratic Republic of the Congo, 2019

The ongoing Ebola outbreak in the eastern Democratic Republic of the Congo is facing unprecedented levels of insecurity and violence. We evaluate the likely impact in terms of added transmissibility and cases of major security incidents in the Butembo coordination hub. We also show that despite this additional burden, an adapted response strategy involving enlarged ring vaccination around clusters of cases and enhanced community engagement managed to bring this main hotspot under control.

Health-related publications on people living in fragile states in the alert zone: a bibliometric analysis

Background

Fragile states pose a global challenge. Assessing health research activity on people living in these states can help identify neglected health domains in fragile settings. The objective of the current study was to assess and describe health research activity on people living in fragile states in the alert zone.

Method

A bibliometric method was applied using SciVerse Scopus. Research articles published on people in fragile states in the alert zone were retrieved and analyzed. The Fragile State Index (FSI) score was used for selection of states in the alert zone. The analysis was limited to 1 year; 2018.

Results

The search query found 2299 research articles giving an average of 2 research articles per one million population per year in the selected fragile states. The number of research articles per one million population was not significantly correlated (p = 0.053; r = − 0.349) with FSI scores. However, it was significantly correlated with the extent of international research collaboration (p < 0.01, r = 065). Research on communicable diseases was the largest research domain (763 articles; 33.2%) followed by maternal/women’s health (430 articles; 18.7%), non-communicable diseases (291 articles; 12.7%), health system/policy (271 articles; 11.8%) and psychosocial and mental health (89; 3.9%). There were three research themes in the research domain of infectious diseases: HIV/AIDS; water-borne infectious diseases; and miscellaneous infectious diseases such as tuberculosis and malaria. The top ten cited articles were mainly on infectious diseases, particularly on malaria and Lassa fever. Of all the retrieved documents, 727 (31.6%) research articles appeared in national/regional journals while the remaining appeared in international journals. The World Health organization was the most active funding organization for research on fragile states. Top ten active institutions were mainly based in fragile states with the lowest FSI score, specifically Ethiopia, Uganda, Nigeria, and Pakistan.

Conclusion

Research on fragile states was relatively low. Research on mental health and health system/policy should be encouraged. Collaboration and funding might help academic institutions in fragile states to make health problems in these countries more visible.

Multi-model forecasts of the ongoing Ebola epidemic in the Democratic Republic of Congo, March-October 2019

The 2018–2020 Ebola outbreak in the Democratic Republic of the Congo is the first to occur in an armed conflict zone. The resulting impact on population movement, treatment centres and surveillance has created an unprecedented challenge for real-time epidemic forecasting. Most standard mathematical models cannot capture the observed incidence trajectory when it deviates from a traditional epidemic logistic curve. We fit seven dynamic models of increasing complexity to the incidence data published in the World Health Organization Situation Reports, after adjusting for reporting delays. These models include a simple logistic model, a Richards model, an endemic Richards model, a double logistic growth model, a multi-model approach and two sub-epidemic models. We analyse model fit to the data and compare real-time forecasts throughout the ongoing epidemic across 29 weeks from 11 March to 23 September 2019. We observe that the modest extensions presented allow for capturing a wide range of epidemic behaviour. The multi-model approach yields the most reliable forecasts on average for this application, and the presented extensions improve model flexibility and forecasting accuracy, even in the context of limited epidemiological data.

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases

The rapid detection of ongoing outbreak – and the identification of causative pathogen – is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors – such as population density, travel, and trade – and ecological factors – like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB^® environment). The IDS has been tested with the epidemiological data of three outbreaks occurred recently: severe acute respiratory syndrome epidemic in China (2002–2003), plague outbreak in Madagascar (2017) and the Ebola virus disease outbreak in the Democratic Republic of Congo (2018). The outcomes are promising and they reveal that the software has been able to recognize and characterize these outbreaks. The future perspective about this software regards the developing of that tool as a useful and user-friendly predictive tool appropriate for first responders, health care workers, and public health decision makers to help them in predicting, assessing and contrasting outbreaks.

An analysis of International Health Regulations Emergency Committees and Public Health Emergency of International Concern Designations

INTRODUCTION

Nine events have been assessed for potential declaration of a Public Health Emergency of International Concern (PHEIC). A PHEIC is defined as an extraordinary event that constitutes a public health risk to other states through international spread and requires a coordinated international response. The WHO Director-General convenes Emergency Committees (ECs) to provide their advice on whether an event constitutes a PHEIC. The EC rationales have been criticised for being non-transparent and contradictory to the International Health Regulations (IHR). This first comprehensive analysis of EC rationale provides recommendations to increase clarity of EC decisions which will strengthen the IHR and WHO's legitimacy in future outbreaks.

METHODS

66 EC statements were reviewed from nine public health outbreaks of influenza A, Middle East respiratory syndrome coronavirus, polio, Ebola virus disease, Zika, yellow fever and coronavirus disease-2019. Statements were analysed to determine which of the three IHR criteria were noted as contributing towards the EC's justification on whether to declare a PHEIC and what language was used to explain the decision.

RESULTS

Interpretation of the criteria were often vague and applied inconsistently. ECs often failed to describe and justify which criteria had been satisfied.

DISCUSSION

Guidelines must be developed for the standardised interpretation of IHR core criteria. The ECs must clearly identify and justify which criteria have contributed to their rationale for or against PHEIC declaration.

CONCLUSION

Striving for more consistency and transparency in EC justifications would benefit future deliberations and provide more understanding and support for the process.

Rigorous surveillance is necessary for high confidence in end-of-outbreak declarations for Ebola and other infectious diseases

The World Health Organization considers an Ebola outbreak to have ended once 42 days have passed since the last possible exposure to a confirmed case. Benefits of a quick end-of-outbreak declaration, such as reductions in trade/travel restrictions, must be balanced against the chance of flare-ups from undetected residual cases. We show how epidemiological modelling can be used to estimate the surveillance level required for decision-makers to be confident that an outbreak is over. Results from a simple model characterizing an Ebola outbreak suggest that a surveillance sensitivity (i.e. case reporting percentage) of 79% is necessary for 95% confidence that an outbreak is over after 42 days without symptomatic cases. With weaker surveillance, unrecognized transmission may still occur: if the surveillance sensitivity is only 40%, then 62 days must be waited for 95% certainty. By quantifying the certainty in end-of-outbreak declarations, public health decision-makers can plan and communicate more effectively. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This issue is linked with the earlier theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

Spatiotemporal variability in case fatality ratios for the 2013-2016 Ebola epidemic in West Africa

BACKGROUND

For the 2013-2016 Ebola epidemic in West Africa, the largest Ebola virus disease (EVD) epidemic to date, we aim to analyse the patient mix in detail to characterise key sources of spatiotemporal heterogeneity in the case fatality ratios (CFR).

METHODS

We applied a non-parametric Boosted Regression Trees (BRT) imputation approach for patients with missing survival outcomes and adjusted for model imperfection. Semivariogram analysis and kriging were used to investigate spatiotemporal heterogeneities.

RESULTS

CFR estimates varied significantly between districts and over time over the course of the epidemic. BRT modelling accounted for most of the spatiotemporal variation and interactions in CFR, but moderate spatial autocorrelation remained for distances up to approximately 90 km. Combining district-level CFR estimates and kriged district-level residuals provided the best linear unbiased predicted map of CFR accounting for the both explained and unexplained spatial variation. Temporal autocorrelation was not observed in the district-level residuals from the BRT estimates.

CONCLUSIONS

This study provides new insight into the epidemiology of the 2013-2016 West African Ebola epidemic with a view of informing future public health contingency planning, resource allocation and impact assessment. The analytical framework developed in this analysis, coupled with key domain knowledge, could be deployed in real time to support the response to ongoing and future outbreaks.

Ebola Virus Disease: Epidemiology, Clinical Features, Management, and Prevention

Ebola virus disease (EVD) is a deadly zoonotic disease caused by the Ebola virus. There is no specific treatment approved for EVD. Supportive care and management of complications are mainstays of treatment. Effective outbreak control requires a multidisciplinary team effort applying case management, infection prevention and control practices, surveillance and contact tracing, a good laboratory service, safe and dignified burials, and social and community mobilization. This article highlights the epidemiology, clinical features, diagnosis, management, and prevention of EVD. The emerging diagnostic technologies, rapid viral characterization, geospatial mapping of EVD transmission, and new treatments and vaccines are discussed.

The Utility of Human Immune System Mice for High-Containment Viral Hemorrhagic Fever Research

Human immune system (HIS) mice are a subset of humanized mice that are generated by xenoengraftment of human immune cells or tissues and/or their progenitors into immunodeficient mice. Viral hemorrhagic fevers (VHFs) cause severe disease in humans, typically with high case fatality rates. HIS mouse studies have been performed to investigate the pathogenesis and immune responses to VHFs that must be handled in high-containment laboratory facilities. Here, we summarize studies on filoviruses, nairoviruses, phenuiviruses, and hantaviruses, and discuss the knowledge gained from using various HIS mouse models. Furthermore, we discuss the complexities of designing and interpreting studies utilizing HIS mice while highlighting additional questions about VHFs that can still be addressed using HIS mouse models.

Ebola virus disease

Ebola virus disease (EVD) is a severe and frequently lethal disease caused by Ebola virus (EBOV). EVD outbreaks typically start from a single case of probable zoonotic transmission, followed by human-to-human transmission via direct contact or contact with infected bodily fluids or contaminated fomites. EVD has a high case-fatality rate; it is characterized by fever, gastrointestinal signs and multiple organ dysfunction syndrome. Diagnosis requires a combination of case definition and laboratory tests, typically real-time reverse transcription PCR to detect viral RNA or rapid diagnostic tests based on immunoassays to detect EBOV antigens. Recent advances in medical countermeasure research resulted in the recent approval of an EBOV-targeted vaccine by European and US regulatory agencies. The results of a randomized clinical trial of investigational therapeutics for EVD demonstrated survival benefits from two monoclonal antibody products targeting the EBOV membrane glycoprotein. New observations emerging from the unprecedented 2013-2016 Western African EVD outbreak (the largest in history) and the ongoing EVD outbreak in the Democratic Republic of the Congo have substantially improved the understanding of EVD and viral persistence in survivors of EVD, resulting in new strategies toward prevention of infection and optimization of clinical management, acute illness outcomes and attendance to the clinical care needs of patients.

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.

The 2018/19 Ebola epidemic the Democratic Republic of the Congo (DRC): epidemiology, outbreak control, and conflict

The Democratic Republic of Congo (DRC) (formerly Zaire) was the location of the first Ebola outbreak, in 1976, and since then there have been a total of ten outbreaks in different parts of the country. The current outbreak, the first in eastern DRC (North Kivu and Ituri provinces), began in July 2018, and by December 2019, there had been 3262 cases and 2232 deaths. Within weeks of the first reported cases, the World Health Organisation (WHO) and the DRC Ministry of Health (MOH) initiated a major response programme, with laboratory support, international agencies providing personnel, and material resources. Unlike previous Ebola outbreaks, including the west Africa epidemic, a proven vaccine, and trial therapeutic agents have been available as part of the outbreak response. Two therapeutic agents, mAb114 and REGN-EB3, both monoclonal antibody derived, have shown case fatality rates (CFR) of around 30%, compared to the overall of 66%. Despite these positive interventions, the outbreak has continued for eighteen months. Underlying the outbreak response has been a high number of violent incidents by local militias, and community mistrust and lack of involvement that has hampered many aspects of the response programme. As a result, many cases are not reported early and not transferred to treatment centres, deaths and increased transmission occur in the community, and the response programme is reaching only a proportion of the cases. New strategies to improve community participation, and integrate the Ebola response into the existing health structure are planned to improve the programme effectiveness.

GILT restricts the cellular entry mediated by the envelope glycoproteins of SARS-CoV, Ebola virus and Lassa fever virus

Interferons (IFNs) control viral infections by inducing expression of IFN-stimulated genes (ISGs) that restrict distinct steps of viral replication. We report herein that gamma-interferon-inducible lysosomal thiol reductase (GILT), a lysosome-associated ISG, restricts the infectious entry of selected enveloped RNA viruses. Specifically, we demonstrated that GILT was constitutively expressed in lung epithelial cells and fibroblasts and its expression could be further induced by type II interferon. While overexpression of GILT inhibited the entry mediated by envelope glycoproteins of SARS coronavirus (SARS-CoV), Ebola virus (EBOV) and Lassa fever virus (LASV), depletion of GILT enhanced the entry mediated by these viral envelope glycoproteins. Furthermore, mutations that impaired the thiol reductase activity or disrupted the N-linked glycosylation, a posttranslational modification essential for its lysosomal localization, largely compromised GILT restriction of viral entry. We also found that the induction of GILT expression reduced the level and activity of cathepsin L, which is required for the entry of these RNA viruses in lysosomes. Our data indicate that GILT is a novel antiviral ISG that specifically inhibits the entry of selected enveloped RNA viruses in lysosomes via disruption of cathepsin L metabolism and function and may play a role in immune control and pathogenesis of these viruses.

Ebola virus disease: An emerging and re-emerging viral threat

The genus Ebolavirus from the family Filoviridae is composed of five species including Sudan ebolavirus, Reston ebolavirus, Bundibugyo ebolavirus, Taï Forest ebolavirus, and Ebola virus (previously known as Zaire ebolavirus). These viruses have a large non-segmented, negative-strand RNA of approximately 19 kb that encodes for glycoproteins (i.e., GP, sGP, ssGP), nucleoproteins, virion proteins (i.e., VP 24, 30,40) and an RNA dependent RNA polymerase. These viruses have become a global health concern because of mortality, their rapid dissemination, new outbreaks in West-Africa, and the emergence of a new condition known as "Post-Ebola virus disease syndrome" that resembles inflammatory and autoimmune conditions such as rheumatoid arthritis, systemic lupus erythematosus and spondyloarthritis with uveitis. However, there are many gaps in the understanding of the mechanisms that may induce the development of such autoimmune-like syndromes. Some of these mechanisms may include a high formation of neutrophil extracellular traps, an uncontrolled "cytokine storm", and the possible formation of auto-antibodies. The likely appearance of autoimmune phenomena in Ebola survivors suppose a new challenge in the management and control of this disease and opens a new field of research in a special subgroup of patients. Herein, the molecular biology, pathogenesis, clinical manifestations, and treatment of Ebola virus disease are reviewed and some strategies for control of disease are discussed.

Improved inference of time-varying reproduction numbers during infectious disease outbreaks

Accurate estimation of the parameters characterising infectious disease transmission is vital for optimising control interventions during epidemics. A valuable metric for assessing the current threat posed by an outbreak is the time-dependent reproduction number, i.e. the expected number of secondary cases caused by each infected individual. This quantity can be estimated using data on the numbers of observed new cases at successive times during an epidemic and the distribution of the serial interval (the time between symptomatic cases in a transmission chain). Some methods for estimating the reproduction number rely on pre-existing estimates of the serial interval distribution and assume that the entire outbreak is driven by local transmission. Here we show that accurate inference of current transmissibility, and the uncertainty associated with this estimate, requires: (i) up-to-date observations of the serial interval to be included, and; (ii) cases arising from local transmission to be distinguished from those imported from elsewhere. We demonstrate how pathogen transmissibility can be inferred appropriately using datasets from outbreaks of H1N1 influenza, Ebola virus disease and Middle-East Respiratory Syndrome. We present a tool for estimating the reproduction number in real-time during infectious disease outbreaks accurately, which is available as an R software package (EpiEstim 2.2). It is also accessible as an interactive, user-friendly online interface (EpiEstim App), permitting its use by non-specialists. Our tool is easy to apply for assessing the transmission potential, and hence informing control, during future outbreaks of a wide range of invading pathogens.

Assessment of a health facility based active case finding system for Ebola virus disease in Mbandaka, Democratic Republic of the Congo, June-July 2018

Background

The ninth outbreak of Ebola Virus Disease (EVD) in the Democratic Republic of the Congo occurred in Équateur Province from 8 May-24 July 2018. A system of health facility (HF)-based active case finding (ACF) was implemented in Mbandaka, a regional capital with four confirmed EVD cases, following completion of contact tracing. The goal of this HF-based ACF system was to look for undetected EVD cases among patients that visited HFs beginning one week prior to the system’s implementation.

Methods

From 23 June – 24 July 2018, ACF teams visited HFs in Mbandaka and reviewed all medical records as far back as 17 June for any consultations meeting the suspected EVD case definition. The teams then assessed whether to validate these as suspected EVD cases based on factors such as recovery, epidemiological links, and their clinical judgement. ACF teams also assessed HFs’ awareness of EVD symptoms and the process for alerting suspected cases. We calculated descriptive statistics regarding the characteristics of reviewed consultations, alert cases, and visited HFs. We also used univariate and multivariate random effects logistic regression models to evaluate the impact of repeated ACF visits to the same HF on the staff’s awareness of EVD.

Results

ACF teams reviewed 37,746 consultations, of which 690 met the definition of a suspected case of EVD. Two were validated as suspected EVD cases and transferred to the Ebola Treatment Unit for testing; both tested negative. Repeated ACF visits to the same HF were significantly associated with improved EVD awareness (p < 0.001) in univariate and multivariate analyses.

Conclusion

HF-based ACF during EVD outbreaks may improve EVD awareness and reveal many individuals meeting the suspected case definition. However, many who meet this definition may not have EVD, depending on the population size covered by ACF and amount of ongoing EVD transmission. Given the burdensome procedure of testing suspected EVD cases, future HF-based ACF systems would benefit from improved clarity on which patients require further testing.

Predicting Ebola virus disease risk and the role of African bat birthing

Ebola virus disease (EVD) presents a threat to public health throughout equatorial Africa. Despite numerous 'spillover' events into humans and apes, the maintenance reservoirs and mechanism of spillover are poorly understood. Evidence suggests fruit bats play a role in both instances, yet data remain sparse and bats exhibit a wide range of life history traits. Here we pool sparse data and use a mechanistic approach to examine how birthing cycles of African fruit bats, molossid bats, and non-molossid microbats inform the spatio-temporal occurrence of EVD spillover. We create ensemble niche models to predict spatio-temporally varying bat birthing and model outbreaks as spatio-temporal Poisson point processes. We predict three distinct annual birthing patterns among African bats along a latitudinal gradient. Of the EVD spillover models tested, the best by quasi-Akaike information criterion (qAIC) and by out of sample prediction included significant African bat birth-related terms. Temporal bat birthing terms fit in the best models for both human and animal outbreaks were consistent with hypothesized viral dynamics in bat populations, but purely spatial models also performed well. Our best model predicted risk of EVD spillover at locations of the two 2018 EVD outbreaks in the Democratic Republic of the Congo was within the top 12-35% and 0.1% of all 25 × 25 km spatial cells analyzed in sub-Saharan Africa. Results suggest that sparse data can be leveraged to help understand complex systems.

Evidence-Based Clinical Management of Ebola Virus Disease and Epidemic Viral Hemorrhagic Fevers

The 2014 to 2016 Ebola virus disease outbreak underscored the threat posed by hemorrhagic fevers. Filoviral outbreaks have been identified since 1967, but data collection has remained sparse, limiting current knowledge of these illnesses. Documentation of objective physical signs and laboratory parameters and appropriate clinical management are connected and interdependent. Implementing both is necessary to improve outcomes. Clinical features include severe volume depletion due to diarrhea and vomiting, shock, rhabdomyolysis, and metabolic disturbances. Overt hemorrhage is uncommon. Point-of-care devices and inexpensive electronic equipment enable better monitoring and record keeping in resource-limited settings.

Joint external evaluation of the International Health Regulation (2005) capacities: current status and lessons learnt in the WHO African region

The International Health Regulations (IHR, 2005) are an essential vehicle for addressing global health security. Here, we report the IHR capacities in the WHO African from independent joint external evaluation (JEE). The JEE is a voluntary component of the IHR monitoring and evaluation framework. It evaluates IHR capacities in 19 technical areas in four broad themes: ‘Prevent’ (7 technical areas, 15 indicators); ‘Detect’ (4 technical areas, 13 indicators); ‘Respond’ (5 technical areas, 14 indicators), points of entry (PoE) and other IHR hazards (chemical and radiation) (3 technical areas, 6 indicators). The IHR capacity scores are graded from level 1 (no capacity) to level 5 (sustainable capacity). From February 2016 to March 2019, 40 of 47 WHO African region countries (81% coverage) evaluated their IHR capacities using the JEE tool. No country had the required IHR capacities. Under the theme ‘Prevent’, no country scored level 5 for 12 of 15 indicators. Over 80% of them scored level 1 or 2 for most indicators. For ‘Detect’, none scored level 5 for 12 of 13 indicators. However, many scored level 3 or 4 for several indicators. For ‘Respond’, none scored level 5 for 13 of 14 indicators, and less than 10% had a national multihazard public health emergency preparedness and response plan. For PoE and other IHR hazards, most countries scored level 1 or 2 and none scored level 5. Countries in the WHO African region are commended for embracing the JEE to assess their IHR capacities. However, major gaps have been identified. Urgent collective action is needed now to protect the WHO African region from health security threats.

Spatial variability in the reproduction number of Ebola virus disease, Democratic Republic of the Congo, January-September 2019

The ongoing Ebola virus disease epidemic (August 2018─October 2019) in the Democratic Republic of the Congo, has been exacerbated by deliberate attacks on healthcare workers despite vaccination efforts. Using a mathematical/statistical modelling framework, we present the quantified effective reproduction number (R_t) at national and regional levels as at 29 September. The weekly trend in R_t displays fluctuations while our recent national-level R_t falls slightly above 1.0 with substantial uncertainty, which suggests improvements in epidemic control.

The monetary value of human lives lost through Ebola virus disease in the Democratic Republic of Congo in 2019

BACKGROUND

Between 8 May 2018 and 27 May 2019, cumulatively there were 1286 deaths from Ebola Virus Disease (EVD) in the Democratic Republic of Congo (DRC). The objective of this study was to estimate the monetary value of human lives lost through EVD in DRC.

METHODS

Human capital approach was applied to monetarily value years of life lost due to premature deaths from EVD. The future losses were discounted to their present values at 3% discount rate. The model was reanalysed using 5 and 10% discount rates. The analysis was done alternately using the average life expectancies for DRC, the world, and the Japanese females to assess the effect on the monetary value of years of life lost (MVYLL).

RESULTS

The 1286 deaths resulted in a total MVYLL of Int$17,761,539 assuming 3% discount rate and DRC life expectancy of 60.5 years. The average monetary value per EVD death was of Int$13,801. About 44.7 and 48.6% of the total MVYLL was borne by children aged below 9 years and adults aged between 15 years and 59 years, respectively. Re-estimation of the algorithm with average life expectancies of the world (both sexes) and Japanese females, holding discount rate constant at 3%, increased the MVYLL by Int$ 3,667,085 (20.6%) and Int$ 7,508,498 (42.3%), respectively. The application of discount rates of 5 and 10%, holding life expectancy constant at 60.5 years, reduced the MVYLL by Int$ 4,252,785 (- 23.9%) and Int$ 9,658,195 (- 54.4%) respectively.

CONCLUSION

The EVD outbreak in DRC led to a considerable MVYLL. There is an urgent need for DRC government and development partners to disburse adequate resources to strengthen the national health system and other systems that address social determinants of health to end recurrence of EVD outbreaks.

Scalable, semi-automated fluorescence reduction neutralization assay for qualitative assessment of Ebola virus-neutralizing antibodies in human clinical samples

Antibody titers against a viral pathogen are typically measured using an antigen binding assay, such as an enzyme-linked immunosorbent assay (ELISA), which only measures the ability of antibodies to identify a viral antigen of interest. Neutralization assays measure the presence of virus-neutralizing antibodies in a sample. Traditional neutralization assays, such as the plaque reduction neutralization test (PRNT), are often difficult to use on a large scale due to being both labor and resource intensive. Here we describe an Ebola virus fluorescence reduction neutralization assay (FRNA), which tests for neutralizing antibodies, that requires only a small volume of sample in a 96-well format and is easy to automate. The readout of the FRNA is the percentage of Ebola virus-infected cells measured with an optical reader or overall chemiluminescence that can be generated by multiple reading platforms. Using blinded human clinical samples (EVD survivors or contacts) obtained in Liberia during the 2013-2016 Ebola virus disease outbreak, we demonstrate there was a high degree of agreement between the FRNA-measured antibody titers and the Filovirus Animal Non-clinical Group (FANG) ELISA titers with the FRNA providing information on the neutralizing capabilities of the antibodies.