The Medecins Sans Frontieres Intervention in the Marburg Hemorrhagic Fever Epidemic, Uige, Angola, 2005. I. Lessons Learned in the Hospital.

When the epidemic of Marburg hemorrhagic fever occurred in Uige, Angola, during 2005, the international response included systems of case detection and isolation, community education, the burial of the dead, and disinfection. However, despite large investments of staff and money by the organizations involved, only a fraction of the reported number of cases were isolated, and many cases were detected only after death. This article describes the response of Medecins Sans Frontieres Spain within the provincial hospital in Uige, as well as the lessons they learned during the epidemic. Diagnosis, management of patients, and infection control activities in the hospital are discussed. To improve the acceptability of the response to the host community, psychological and cultural factors need to be considered at all stages of planning and implementation in the isolation ward. More interventional medical care may not only improve survival but also improve acceptability

Clinical Manifestations and Case Management of Ebola Haemorrhagic Fever caused by a newly identified virus strain, Bundibugyo, Uganda, 2007-2008

A confirmed Ebola haemorrhagic fever (EHF) outbreak in Bundibugyo, Uganda, November 2007-February 2008, was caused by a putative new species (Bundibugyo ebolavirus). It included 93 putative cases, 56 laboratory-confirmed cases, and 37 deaths (CFR = 25%). Study objectives are to describe clinical manifestations and case management for 26 hospitalised laboratory-confirmed EHF patients. Clinical findings are congruous with previously reported EHF infections. The most frequently experienced symptoms were non-bloody diarrhoea (81%), severe headache (81%), and asthenia (77%). Seven patients reported or were observed with haemorrhagic symptoms, six of whom died. Ebola care remains difficult due to the resource-poor setting of outbreaks and the infection-control procedures required. However, quality data collection is essential to evaluate case definitions and therapeutic interventions, and needs improvement in future epidemics. Organizations usually involved in EHF case management have a particular responsibility in this respect

Essentials of Filoviral Load Quantification

Quantitative measurement of viral load is an important parameter in the management of filovirus disease outbreaks because viral load correlates with severity of disease, survival, and infectivity. During the ongoing Ebola virus disease outbreak in parts of Western Africa, most assays used in the detection of Ebola virus disease by more than 44 diagnostic laboratories yielded qualitative results. Regulatory hurdles involved in validating quantitative assays and the urgent need for a rapid Ebola virus disease diagnosis precluded development of validated quantitative assays during the outbreak. Because of sparse quantitative data obtained from these outbreaks, opportunities for study of correlations between patient outcome, changes in viral load during the course of an outbreak, disease course in asymptomatic individuals, and the potential for virus transmission between infected patients and contacts have been limited. We strongly urge the continued development of quantitative viral load assays to carefully evaluate these parameters in future outbreaks of filovirus disease

Presence and Persistence of Ebola or Marburg Virus in Patients and Survivors: A Rapid Systematic Review

Background: The 2013-15 Ebola outbreak was unprecedented due to sustainedtransmission within urban environments and thousands of survivors. In 2014 the World Health Organization stated that there was insufficient evidence to give definitive guidance about which body fluids are infectious and when they pose a risk to humans. We report a rapid systematic review of published evidence on the presence of filoviruses in body fluids of infected people and survivors. Methods: Scientific articles were screened for information about filovirus in human body fluids. The aim was to find primary data that suggested high likelihood of actively infectious filovirus in human body fluids (viral RNA). Eligible infections were from Marburg virus (MARV or RAVV) and Zaire, Sudan, Taï Forest and Bundibugyo species of Ebola. [1] Cause of infection had to be laboratory confirmed (in practice either tissue culture or RT-PCR tests), or evidenced by compatible clinical history with subsequent positivity for filovirus antibodies or inflammatory factors. Data were extracted and summarized narratively. Results: 6831 unique articles were found, and after screening, 33 studies were eligible. For most body fluid types there were insufficient patients to draw strong conclusions, and prevalence of positivity was highly variable. Body fluids taken >16 days after onset were usually negative. In the six studies that used both assay methods RT-PCR tests for filovirus RNA gave positive results about 4 times more often than tissue culture. Conclusions: Filovirus was reported in most types of body fluid, but not in every sample from every otherwise confirmed patient. Apart from semen, most non-blood, RT-PCR positive samples are likely to be culture negative and so possibly of low infectious risk. Nevertheless, it is not apparent how relatively infectious many body fluids are during or after illness, even when culture-positive, not least because most test results come from more severe cases. Contact with blood and blood-stained body fluids remains the major risk for disease transmission because of the known high viral loads in blood

The Use of a Mobile Laboratory Unit in Support of Patient Management and Epidemiological Surveillance during the 2005 Marburg Outbreak in Angola

A mobile laboratory unit (MLU) was deployed to Uige, Angola as part of the World Health Organization response to an outbreak of viral hemorrhagic fever caused by Marburg virus (MARV). Utilizing mainly quantitative real-time PCR assays, this laboratory provided specific MARV diagnostics in the field. The MLU operated for 88 consecutive days allowing MARV-specific diagnostic response in <4 hours from sample receiving. Most cases were found among females in the child-bearing age and in children less than five years of age including a high number of paediatric cases implicating breastfeeding as potential transmission route. Oral swabs were identified as a useful alternative specimen source to the standard whole blood/serum specimens for patients refusing blood draw. There was a high concordance in test results between the MLU and the reference laboratory in Luanda operated by the US Centers for Disease Control and Prevention. The MLU was an important outbreak response asset providing valuable support in patient management and epidemiological surveillance. Field laboratory capacity should be expanded and made an essential part of any future outbreak investigation

Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health

Impact of two interventions on timeliness and data quality of an electronic disease surveillance system in a resource limited setting (Peru): a prospective evaluation

<p>Abstract</p> <p>Background</p> <p>A timely detection of outbreaks through surveillance is needed in order to prevent future pandemics. However, current surveillance systems may not be prepared to accomplish this goal, especially in resource limited settings. As data quality and timeliness are attributes that improve outbreak detection capacity, we assessed the effect of two interventions on such attributes in Alerta, an electronic disease surveillance system in the Peruvian Navy.</p> <p>Methods</p> <p>40 Alerta reporting units (18 clinics and 22 ships) were included in a 12-week prospective evaluation project. After a short refresher course on the notification process, units were randomly assigned to either a phone, visit or control group. Phone group sites were called three hours before the biweekly reporting deadline if they had not sent their report. Visit group sites received supervision visits on weeks 4 & 8, but no phone calls. The control group sites were not contacted by phone or visited. Timeliness and data quality were assessed by calculating the percentage of reports sent on time and percentage of errors per total number of reports, respectively.</p> <p>Results</p> <p>Timeliness improved in the phone group from 64.6% to 84% in clinics (+19.4 [95% CI, +10.3 to +28.6]; p < 0.001) and from 46.9% to 77.3% on ships (+30.4 [95% CI, +16.9 to +43.8]; p < 0.001). Visit and control groups did not show significant changes in timeliness. Error rates decreased in the visit group from 7.1% to 2% in clinics (-5.1 [95% CI, -8.7 to -1.4]; p = 0.007), but only from 7.3% to 6.7% on ships (-0.6 [95% CI, -2.4 to +1.1]; p = 0.445). Phone and control groups did not show significant improvement in data quality.</p> <p>Conclusion</p> <p>Regular phone reminders significantly improved timeliness of reports in clinics and ships, whereas supervision visits led to improved data quality only among clinics. Further investigations are needed to establish the cost-effectiveness and optimal use of each of these strategies.</p