The effectiveness of screening travellers during times of international disease outbreak is contentious, especially as the reduction in the risk of disease importation can be very small. Border screening typically consists of travellers being thermally scanned for signs of fever and/or completing a survey declaring any possible symptoms prior to admission to their destination country; while more thorough testing typically exists, these would generally prove more disruptive to deploy. In this paper, we describe a simple Monte Carlo based model that incorporates the epidemiology of coronavirus disease-2019 (COVID-19) to investigate the potential decrease in risk of disease importation that might be achieved by requiring travellers to undergo screening upon arrival during the current pandemic. This is a purely theoretical study to investigate the maximum impact that might be attained by deploying a test or testing programme simply at the point of entry, through which we may assess such action in the real world as a method of decreasing the risk of importation. We, therefore, assume ideal conditions such as 100% compliance among travellers and the use of a ‘perfect’ test. In addition to COVID-19, we also apply the presented model to simulated outbreaks of influenza, severe acute respiratory syndrome (SARS) and Ebola for comparison. Our model only considers screening implemented at airports, being the predominant method of international travel. Primary results showed that in the best-case scenario, screening at the point of entry may detect a maximum of 8.8% of travellers infected with COVID-19, compared to 34.8.%, 9.7% and 3.0% for travellers infected with influenza, SARS and Ebola respectively. While results appear to indicate that screening is more effective at preventing disease ingress when the disease in question has a shorter average incubation period, our results suggest that screening at the point of entry alone does not represent a sufficient method to adequately protect a nation from the importation of COVID-19 cases.

The capacity to rapidly distinguish Ebola virus disease from other infectious diseases and to monitor biochemistry and viremia levels is crucial to the clinical management of suspected Ebola virus disease cases. This article describes the design and practical considerations of a laboratory straddling the high- and low-risk zones of an Ebola treatment center to produce timely diagnostic and clinical results for informed case management of Ebola virus disease in real-life conditions. This innovation may be of relevance for actors requiring flexible laboratory implementation in contexts of high-communicability, high-lethality disease outbreaks.

In Sierra Leone, the Ebola virus disease (EVD) outbreak occurred with substantial differences between districts with someone even not affected. To monitor the epidemic, a community event-based surveillance system was set up, collecting data into the Viral Haemorrhagic Fever (VHF) database. We analysed the VHF database of Tonkolili district to describe the epidemiology of the EVD outbreak during July 2014–June 2015 (data availability). Multivariable analysis was used to identify risk factors for EVD, fatal EVD and barriers to healthcare access, by comparing EVD-positive vs. EVD-negative cases. Key-performance indicators for EVD response were also measured. Overall, 454 EVD-positive cases were reported. At multivariable analysis, the odds of EVD was higher among those reporting contacts with an EVD-positive/suspected case (odds ratio (OR) 2.47; 95% confidence interval (CI) 2.44–2.50; P < 0.01) and those attending funeral (OR 1.02; 95% CI 1.01–1.04; P < 0.01). EVD cases from Kunike chiefdom had a lower odds of death (OR 0.22; 95% CI 0.08–0.44; P < 0.01) and were also more likely to be hospitalised (OR 2.34; 95% CI 1.23–4.57; P < 0.05). Only 25.1% of alerts were generated within 1 day from symptom onset. EVD preparedness and response plans for Tonkolili should include social-mobilisation activities targeting Ebola/knowledge-attitudes-practice during funeral attendance, to avoid contact with suspected cases and to increase awareness on EVD symptoms, in order to reduce delays between symptom onset to alert generation and consequently improve the outbreak-response promptness.

In early October 2014, 7 months after the 2014–2015 Ebola epidemic in West Africa began, a cluster of reported deaths in Koinadugu, a remote district of Sierra Leone, was the first evidence of Ebola virus disease (Ebola) in the district. Prior to this event, geographic isolation was thought to have prevented the introduction of Ebola to this area. We describe our initial investigation of this cluster of deaths and subsequent public health actions after Ebola was confirmed, and present challenges to our investigation and methods of overcoming them. We present a transmission tree and results of whole genome sequencing of selected isolates to identify the source of infection in Koinadugu and demonstrate transmission between its villages. Koinadugu's experience highlights the danger of assuming that remote location and geographic isolation can prevent the spread of Ebola, but also demonstrates how deployment of rapid field response teams can help limit spread once Ebola is detected.

Understanding infection dynamics in animal hosts is fundamental to managing spillover and emergence of zoonotic infections. Hendra virus is endemic in Australian pteropodid bat populations and can be lethal to horses and humans. However, we know little about the factors driving Hendra virus prevalence in resevoir bat populations, making spillover difficult to predict. We use Hendra virus prevalence data collected from 13 000 pooled bat urine samples across space and time to determine if pulses of prevalence are periodic and synchronized across sites. We also test whether site-specific precipitation and temperature affect the amplitude of the largest annual prevalence pulses. We found little evidence for a periodic signal in Hendra virus prevalence. Although the largest amplitude pulses tended to occur over winter, pulses could also occur in other seasons. We found that Hendra virus prevalence was weakly synchronized across sites over short distances, suggesting that prevalence is driven by local-scale effects. Finally, we found that drier conditions in previous seasons and the abundance of Pteropus alecto were positively correlated with the peak annual values of Hendra virus prevalence. Our results suggest that in addition to seasonal effects, bat density and local climatic conditions interact to drive Hendra virus infection dynamics.

During the recent Ebola crisis in West Africa, individual person-level details of disease onset, transmissions, and outcomes such as survival or death were reported in online news media. We set out to document disease transmission chains for Ebola, with the goal of generating a timely account that could be used for surveillance, mathematical modeling, and public health decision-making. By accessing public web pages only, such as locally produced newspapers and blogs, we created a transmission chain involving two Ebola clusters in West Africa that compared favorably with other published transmission chains, and derived parameters for a mathematical model of Ebola disease transmission that were not statistically different from those derived from published sources. We present a protocol for responsibly gleaning epidemiological facts, transmission model parameters, and useful details from affected communities using mostly indigenously produced sources. After comparing our transmission parameters to published parameters, we discuss additional benefits of our method, such as gaining practical information about the affected community, its infrastructure, politics, and culture. We also briefly compare our method to similar efforts that used mostly non-indigenous online sources to generate epidemiological information.

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 (R0), serial interval, latent period, infectious period and case fatality rate, and examined their relationships. The median of the estimated mean R0 values were between 1·30 and 1·84 in Sierra Leone, Liberia and Guinea. Much higher R0 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 R0 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 R0 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.

Background: An epidemic of Ebola virus disease (EVD) occurred in West Africa in 2014. In Catalonia, primary care is the first level of healthcare so it has a key role in the detection and initial management of possible cases of EVD and in identifying contacts. Aim: This study aimed to find out how the staff of primary care centers perceived the measures for dealing with EVD. Method: An online questionnaire was distributed to all primary care workers in Catalonia during the period February–March 2015. Findings: The estimated response rate was 10.1%. They reported having received training/information, that a specific circuit had been organized and that the necessary equipment was available. They considered it unlikely that a patient with suspected EVD would present at the center and were aware of the action to take but were worried about this possibility. Rigorous scientific training in international health is essential to take on new global health challenges.

The Ebola virus disease (EVD) outbreak in West Africa may affect healthcare attendance. We describe, in the Guinean prefecture of Guéckédou, trends in attendance of public healthcare structures and the main reported diagnoses over the year following the EVD outbreak notification (March 2014). Monthly numbers of visits and main diagnoses such as malaria, schistosomiasis and measles reported by Guéckédou health centres and health posts were described from January 2012 to March 2015. The median number of visits was 15 724/month. From 1 April to 30 September 2014 (EVD outbreak peak), 90 947 visits were reported, representing decreases of 4·8% and 7·4% compared to 2013 and 2012, respectively. Following December 2014 (last EVD notification in Guéckédou), visits increased from 12 540 in January to 16 032 in March 2015. Malaria seasonality was observed in 2014 with 22 519 notifications from 1 April to 31 July. No seasonality was observed for intestinal schistosomiasis (median 485 cases/month); however, a peak was notified in March 2014 (824 cases). Over the study period, all measles cases were notified in 2015 (183 cases). Reduction in healthcare attendance in Guéckédou was modest during the EVD outbreak. Enhanced infectious disease surveillance is a challenge in this context, due to the impact of EVD on traditional prevention programmes.

The 2014 Ebola epidemic was the largest on record. It evidenced the need for improved models of the spread of Ebola. In this research we focus on modelling Ebola within a small village or community. Specifically, we investigate the potential of basic Susceptible-Exposed-Infectious-Recovered (SEIR) models to describe the initial Ebola outbreak, which occurred in Meliandou, Guinea. Data from the World Health Organization is used to compare the accuracy of various models in order to select the most accurate models of transmission and disease-induced responses. Our results suggest that (i) density-dependent transmission and mortality-induced behavioural changes shaped the course of the Ebola epidemic in Meliandou, while (ii) frequency-dependent transmission, disease-induced emigration, and infection-induced behavioural changes are not consistent with the data from this epidemic.

The aim of this study was to review the current evidence regarding the persistence of Ebola virus (EBOV) in various body fluids during convalescence and discuss its implication on disease transmission and control. We conducted a systematic review and searched articles from Medline and EMBASE using key words. We included studies that examined the persistence of EBOV in various body fluids during the convalescent phase. Twelve studies examined the persistence of EBOV in body fluids, with around 800 specimens tested in total. Available evidence suggests that EBOV can persist in some body fluids after clinical recovery and clearance of virus from the blood. EBOV has been isolated from semen, aqueous humor, urine and breast milk 82, 63, 26 and 15 days after onset of illness, respectively. Viral RNA has been detectable in semen (day 272), aqueous humor (day 63), sweat (day 40), urine (day 30), vaginal secretions (day 33), conjunctival fluid (day 22), faeces (day 19) and breast milk (day 17). Given high case fatality and uncertainties around the transmission characteristics, patients should be considered potentially infectious for a period of time after immediate clinical recovery. Patients and their immediate contacts should be informed about these risks. Convalescent patients may need to abstain from sex for at least 9 months or should use condoms until their semen tests are negative. Breastfeeding should be avoided during the convalescent phase. There is a need for more research on persistence, and a uniform approach to infection control guidelines in convalescence.

Mathematical modelling is an important tool for understanding the dynamics of the spread of infectious diseases, which could be the result of a natural outbreak or of the intentional release of pathogenic biological agents. Decision makers and policymakers responsible for strategies to contain disease, prevent epidemics and fight possible bioterrorism attacks, need accurate computational tools, based on mathematical modelling, for preventing or even managing these complex situations. In this article, we tested the validity, and demonstrate the reliability, of an open-source software, the Spatio-Temporal Epidemiological Modeler (STEM), designed to help scientists and public health officials to evaluate and create models of emerging infectious diseases, analysing three real cases of Ebola haemorrhagic fever (EHF) outbreaks: Uganda (2000), Gabon (2001) and Guinea (2014). We discuss the cases analysed through the simulation results obtained with STEM in order to demonstrate the capability of this software in helping decision makers plan interventions in case of biological emergencies.

The current Ebola virus disease (EVD) epidemic in West Africa is unprecedented in scale, and Sierra Leone is the most severely affected country. The case fatality risk (CFR) and hospitalization fatality risk (HFR) were used to characterize the severity of infections in confirmed and probable EVD cases in Sierra Leone. Proportional hazards regression models were used to investigate factors associated with the risk of death in EVD cases. In total, there were 17 318 EVD cases reported in Sierra Leone from 23 May 2014 to 31 January 2015. Of the probable and confirmed EVD cases with a reported final outcome, a total of 2536 deaths and 886 recoveries were reported. CFR and HFR estimates were 74·2% [95% credibility interval (CrI) 72·6–75·5] and 68·9% (95% CrI 66·2–71·6), respectively. Risks of death were higher in the youngest (0–4 years) and oldest (⩾60 years) age groups, and in the calendar month of October 2014. Sex and occupational status did not significantly affect the mortality of EVD. The CFR and HFR estimates of EVD were very high in Sierra Leone.

Nongovernmental organizations (NGOs) play a critical humanitarian role in the developing world. Over 100 NGOs currently operate in Sierra Leone, a country in West Africa that ranks 183 out of 187 in the United Nation’s Human Development Index. Following a brutal 11-year war that ended in January 2002, the country has been unsuccessful at building a sufficiently resourced, robust, and anticipatory public health and medical care infrastructure. Consequently, Sierra Leone suffers from high levels of poverty, infant mortality, and limited access to safe drinking water, as well as morbidity from malnutrition, diarrheal diseases, hepatitis A, cholera, and typhoid fever. Large international NGOs such as Doctors Without Borders have attempted to fill the void left by fragile and fragmented government health services but have been overwhelmed and saturated by the continual spread of Ebola virus disease and growing numbers of cases and deaths. Smaller NGOs endeavored to assist during this crisis as well. One of them, Caritas, has actively sought public health knowledge and has applied public health principles to reduce and contain Ebola virus disease transmission. The Ebola outbreak illuminates the importance of building basic public health capabilities within the core competences of NGOs.(Disaster Med Public Health Preparedness. 2015;9:554–557)

In 2004 the Ebola virus caused a drastic decline in western gorilla Gorilla gorilla abundance at Lokoué Bai, a clearing in Odzala National Park, Republic of Congo. This decline was detected by observations of gorillas visiting the clearing. We confirm that the sympatric chimpanzee Pan troglodytes population was also affected by the Ebola outbreak, and test whether the decline in the ape population would have been detected with line-transect surveys, the most commonly used wildlife monitoring methodology in Central Africa. We also evaluate the potential of transect surveys for describing the extent and pinpointing the timing of drastic population declines when this information is not known from other evidence. Both nest survey using the marked nest count method and standing stock survey of other signs of ape presence (dung, feeding remains, prints) were able to detect the decline. However, only nests and dung were reliable indices for estimating the magnitude of the decline and accurately pinpointing the timing. It was necessary to pool data across many survey replicates because of small samples sizes. Our results suggest that transects methods are able to detect drastic changes in ape abundance but that large sample sizes are necessary to achieve adequate statistical power. We therefore recommend that those intending to use transect methods as tools for monitoring large forest mammals evaluate in advance how much effort will be necessary to detect meaningful changes in animal abundance.

Ebola virus (EBOV) gained public notoriety in the last decade largely as a consequence of the highly publicised isolation of a new EBOV species in a suburb of Washington, DC, in 1989, together with the dramatic clinical presentation of EBOV infection and high case-fatality rate in Africa (near 90% in some outbreaks), and the unusual and striking morphology of the virus. Furthermore, there are no vaccines or effective therapies currently available. Progress in understanding the origins of the pathophysiological changes that make EBOV infections of humans so devastating has been slow, primarily because these viruses require special containment for safe research. However, an increasing understanding of the mechanisms of EBOV pathogenesis, facilitated by the development of new tools to elucidate critical regulatory elements in the viral life cycle, is providing new targets that can be exploited for therapeutic interventions. Notably, identifying factors triggering the haemorrhagic complications that characterise EBOV infections led to the development of a strategy to modulate coagulopathy; this therapeutic modality successfully mitigated the effects of EBOV haemorrhagic fever in nonhuman primates. This review summarises our current understanding of EBOV pathogenesis and discusses various approaches to therapeutic intervention based on our current understanding of how EBOV produces a lethal infection.

Kamedo is a Swedish Disaster Medicine study organization that sends observers to disaster areas anywhere in the world to study recent events, collect useful information, and identify problems relative to the practice of Disaster Medicine. The results of these investigations are published in the KAMEDO Reports, and the English versions will be published in Prehospital and Disaster Medicine.

Three of the recent reports follow: 1) KAMEDO Report 69: Ebolus Virus Epidemic in Zaire, 1995; 2) KAMEDO Report 70: The German Rescue and Emergency Organizations: a) Industrial Chemical Fire, Memmingen, Germany 23 January 1997; b) Fire at the Düsseldorf Airport, 01 April 1996; and c) Bus Accident on the Autobahn in Rosenheim, Germany; and 3) Terrorist Attack with Sarin, 20 March 1995. In addition, a catalog listing all of the KAMEDO Reports available in English is provided.