Participatory systems for surveillance of acute respiratory infection give real-time information about infections circulating in the community, yet to-date are limited to self-reported syndromic information only and lacking methods of linking symptom reports to infection types. We developed the GoViral platform to evaluate whether a cohort of lay volunteers could, and would find it useful to, contribute self-reported symptoms online and to compare specimen types for self-collected diagnostic information of sufficient quality for respiratory infection surveillance. Volunteers were recruited, given a kit (collection materials and customized instructions), instructed to report their symptoms weekly, and when sick with cold or flu-like symptoms, requested to collect specimens (saliva and nasal swab). We compared specimen types for respiratory virus detection sensitivity (via polymerase-chain-reaction) and ease of collection. Participants were surveyed to determine receptivity to participating when sick, to receiving information on the type of pathogen causing their infection and types circulating near them. Between December 1 2013 and March 1 2014, 295 participants enrolled in the study and received a kit. Of those who reported symptoms, half (71) collected and sent specimens for analysis. Participants submitted kits on average 2.30 days (95 CI: 1.65 to 2.96) after symptoms began. We found good concordance between nasal and saliva specimens for multiple pathogens, with few discrepancies. Individuals report that saliva collection is easiest and report that receiving information about what pathogen they, and those near them, have is valued and can shape public health behaviors. Community-submitted specimens can be used for the detection of acute respiratory infection with individuals showing receptivity for participating and interest in a real-time picture of respiratory pathogens near them.
The West Africa Ebola virus epidemic now appears to be coming to an end. In the proposed model, we simulate changes in population behavior that help to explain the observed transmission dynamics. We introduce an EVD transmission model accompanied by a model of social mobilization. The model was fit to Lofa County, Liberia through October 2014, using weekly counts of new cases reported by the US CDC. In simulation studies, we analyze the dynamics of the disease transmission with and without population behavior change, given the availability of beds in Ebola treatment units (ETUs) estimated from observed data. Only the model scenario that included individuals’ behavioral change achieved a good fit to the observed case counts. Although the capacity of the Lofa County ETUs greatly increased in mid-August, our simulations show that the expansion was insufficient to alone control the outbreak. Modeling the entire outbreak without considering behavior change fit the data poorly, and extrapolating from early data without taking behavioral changes into account led to a prediction of exponential outbreak growth, contrary to the observed decline. Education and awareness-induced behavior change in the population was instrumental in curtailing the Ebola outbreak in Lofa County and is likely playing an important role in stopping the West Africa epidemic altogether.
The recent increase in measles cases in California may raise questions regarding the continuing success of measles control. To determine whether the dynamics of measles is qualitatively different in comparison to previous years, we assess whether the 2014-2015 measles outbreak associated with an Anaheim theme park is consistent with subcriticality by calculating maximum-likelihood estimates for the effective reproduction number given this year’s outbreak, using the Galton-Watson branching process model. We find that the dynamics after the initial transmission event are consistent with prior transmission, but does not exclude the possibility that the effective reproduction number has increased.
Ebola Virus Disease (EVD) outbreak was confirmed in Liberia on March 31st 2014. A response comprising of diverse expertise was mobilized and deployed to the country to contain transmission of Ebola and give relief to a people already impoverished from protracted civil war. This paper describes the epidemiological and surveillance response to the EVD outbreak in Lofa County in Liberia from March to September 2014. Five of the 6 districts of Lofa were affected. The most affected districts were Voinjama/Guardu Gbondi and Foya. By 26th September, 2014, a total of 619 cases, including 19.4% probable cases, 20.3% suspected cases and 44.2% confirmed cases were recorded by the Ebola Emergency Response Team (EERT) of Lofa County. Adults (20-50 years) were the most affected. Overall fatality rate was 53.3%. Twenty two (22) cases were reported among the Health Care Workers with a fatality rate of 81.8%. Seventy eight percent (78%) of the contacts successfully completed 21 days follow-up while 134 (6.15%) that developed signs and symptoms of EVD were referred to the ETU in Foya. The contributions of the weak health systems as well as socio-cultural factors in fueling the epidemic are highlighted. Importantly, the lessons learnt including the positive impact of multi-sectorial and multidisciplinary and coordinated response led by the government and community. Again, given that the spread of infectious disease can be considered a security threat every effort has to put in place to strengthen the health systems in developing countries including the International Health Regulation (IHR)’s core capacities.
Key words: Ebola virus disease, outbreak, epidemiology and surveillance, socio-cultural factors, health system, West Africa.
In this commentary, we consider the relationship between early outbreak changes in the observed reproductive number of Ebola in West Africa and various media reported interventions and aggravating events. We find that media reports of interventions that provided education, minimized contact, or strengthened healthcare were typically followed by sustained transmission reductions in both Sierra Leone and Liberia. Meanwhile, media reports of aggravating events generally preceded temporary transmission increases in both countries. Given these preliminary findings, we conclude that media reported events could potentially be incorporated into future epidemic modeling efforts to improve mid-outbreak case projections.
Since Ebola Virus Disease (EVD) was first identified in 1976 in what is now the Democratic Republic of Congo, and despite the numerous outbreaks recorded to date, rarely has an epidemic origin been identified. Indeed, among the twenty-one most documented EVD outbreaks in Africa, an index case has been identified four times, and hypothesized in only two other instances. The initial steps of emergence and spread of a virus are critical in the development of a potential outbreak and need to be thoroughly dissected and understood in order to improve on preventative strategies. In the current West African outbreak of EVD, a unique index case has been identified, pinpointing the geographical origin of the epidemic in Guinea. Herein, we provide an accounting of events that serve as the footprint of EVD emergence in Sierra Leone and a road map for risk mitigation fueled by lessons learned.
The magnitude of the Ebola outbreak in West Africa is unprecedented. Liberia, Guinea, and Sierra Leone are in the bottom ten countries in the Human Development Index, but all had made gains in child survival prior to the outbreak. With closure of healthcare facilities and the loss of health workers secondary to the outbreak, the region risks reversing survival gains achieved in maternal and newborn health.
Anonymized service utilization data were downloaded from the Liberia District Health Information Software (DHIS) 2 for selected maternal health services at PHC facilities in Margibi and Bong Counties from March 2014, when the first case of Ebola was reported in Liberia, through December 2014. Absolute numbers are provided instead of percentage measures because of the lack of a population-based denominator.
Overall, the data show a decrease in absolute utilization from the start of the outbreak, followed by a slow recovery after October or November. In Bong County, totals were less than 14% of the peak numbers during the outbreak for number of antenatal visits and pregnant women receiving intermittent preventive treatment for malaria in pregnancy (IPTp). For total deliveries, utilization was less than 33% of the highest month. In Margibi County, during what now appears to be the height of the outbreak, numbers dropped to less than 9% of peak utilization for antenatal care visits and 4% for IPTp. Total health facility deliveries dropped to less than 9% of peak utilization.
It is clear that Bong and Margibi Counties in Liberia experienced a large drop in utilization of maternal health care services during what now appears to be the peak of the Ebola outbreak. As the health of women and their babies is being promoted in the post-2015 sustainable development agenda, it is critical that the issue of maternal and newborn survival in humanitarian emergency settings, like the Ebola outbreak, is prioritized.
Influenza A viruses in swine cause considerable economic losses and raise concerns about their zoonotic potential. The current paucity of thorough empirical assessments of influenza A virus infection levels in swine herds under different control interventions hinders our understanding of their effectiveness. Between 2012 and 2013, recurrent outbreaks of respiratory disease caused by a reassortant pandemic 2009 H1N1 (H1N1pdm) virus were registered in a swine breeding farm in North-East Italy, providing the opportunity to assess an outbreak response plan based on vaccination and enhanced farm management. All sows/gilts were vaccinated with a H1N1pdm-specific vaccine, biosecurity was enhanced, weaning cycles were lengthened, and cross-fostering of piglets was banned. All tested piglets had maternally-derived antibodies at 30 days of age and were detectable in 5.3% of ~90 day-old piglets. There was a significant reduction in H1N1pdm RT-PCR detections after the intervention. Although our study could not fully determine the extent to which the observed trends in seropositivity or RT-PCR positivity among piglets were due to the intervention or to the natural course of the disease in the herd, we provided suggestive evidence that the applied measures were useful in controlling the outbreak, even without an all-in/all-out system, while keeping farm productivity at full.
Background: The first ever outbreak of Ebola virus disease (EVD) in Nigeria was declared in July, 2014. Level of public knowledge, perception and adequacy of information on EVD were unknown. We assessed the public preparedness level to adopt disease preventive behavior which is premised on appropriate knowledge, perception and adequate information.
Methods: We enrolled 5,322 respondents in a community-based cross-sectional study. We used interviewer-administered questionnaire to collect data on socio-demographic characteristics, EVD–related knowledge, perception and source of information. We performed univariate and bivariate data analysis using Epi-Info software setting p-value of 0.05 as cut-off for statistical significance.
Results: Mean age of respondents was 34 years (± 11.4 years), 52.3% were males. Forty one percent possessed satisfactory general knowledge; 44% and 43.1% possessed satisfactory knowledge on mode of spread and preventive measures, respectively. Residing in EVD cases districts, male respondents and possessing at least secondary education were positively associated with satisfactory general knowledge (p-value: 0.01, 0.001 and 0.000004, respectively). Seventy one percent perceived EVD as a public health problem while 61% believed they cannot contract the disease. Sixty two percent and 64% of respondents will not shake hands and hug a successfully treated EVD patient respectively. Only 2.2% of respondents practice good hand-washing practice. Television (68.8%) and radio (55.0%) are the most common sources of information on EVD.
Conclusions: Gaps in EVD-related knowledge and perception exist. Targeted public health messages to raise knowledge level, correct misconception and discourage stigmatization should be widely disseminated, with television and radio as media of choice.
We developed an agent-based model to investigate the epidemic dynamics of Ebola virus disease (EVD) in Liberia and Sierra Leone from May 27 to December 21, 2014. The dynamics of the agent-based simulator evolve on small-world transmission networks of sizes equal to the population of each country, with adjustable densities to account for the effects of public health intervention policies and individual behavioral responses to the evolving epidemic. Based on time series of the official case counts from the World Health Organization (WHO), we provide estimates for key epidemiological variables by employing the so-called Equation-Free approach. The underlying transmission networks were characterized by rather random structures in the two countries with densities decreasing by ~19% from the early (May 27-early August) to the last period (mid October-December 21). Our estimates for the values of key epidemiological variables, such as the mean time to death, recovery and the case fatality rate, are very close to the ones reported by the WHO Ebola response team during the early period of the epidemic (until September 14) that were calculated based on clinical data. Specifically, regarding the effective reproductive number Re, our analysis suggests that until mid October, Re was above 2.3 in both countries; from mid October to December 21, Re dropped well below unity in Liberia, indicating a saturation of the epidemic, while in Sierra Leone it was around 1.9, indicating an ongoing epidemic. Accordingly, a ten-week projection from December 21 estimated that the epidemic will fade out in Liberia in early March; in contrast, our results flashed a note of caution for Sierra Leone since the cumulative number of cases could reach as high as 18,000, and the number of deaths might exceed 5,000, by early March 2015. However, by processing the reported data of the very last period (December 21, 2014-January 18, 2015), we obtained more optimistic estimates indicative of a remission of the epidemic in Sierra Leone, as reflected by the derived Re (~0.82, 95% CI: 0.81-0.83).