Comparison of predictive models for hepatitis C co-infection among HIV patients in Cambodia.

BACKGROUND: Hepatitis C virus (HCV) infection is a major global health problem. WHO guidelines recommend screening all people living with HIV for hepatitis C. Considering the limited resources for health in low and middle income countries, targeted HCV screening is potentially a more feasible screening strategy for many HIV cohorts. Hence there is an interest in developing clinician-friendly tools for selecting subgroups of HIV patients for whom HCV testing should be prioritized. Several statistical methods have been developed to predict a binary outcome. Multiple studies have compared the performance of different predictive models, but results were inconsistent. METHODS: A cross-sectional HCV diagnostic study was conducted in the HIV cohort of Sihanouk Hospital Center of Hope in Phnom Penh, Cambodia. We compared the performance of logistic regression, Spiegelhalter-Knill-Jones and CART to predict Hepatitis C co-infection in this cohort. We estimated the number of HCV co-infections that would be missed. To correct for over-optimism, the leave-one-out bootstrap estimator was used for estimating this quantity. RESULTS: Logistic regression misses the fewest HCV co-infections (8%), but would still refer 98% of HIV patients for HCV testing. Spiegelhalter-Knill-Jones (SKJ) and CART respectively miss 12% and 29% of HCV co-infections but would only refer about 30% for HCV testing. CONCLUSIONS: In our dataset, logistic regression has the highest log-likelihood and smallest proportions of HCV co-infections missed but Spiegelhalter-Knill-Jones has the highest area under the ROC curve. The likelihood ratios estimated by Spiegelhalter-Knill-Jones might be easier to interpret for clinicians than odds ratios estimated by logistic regression or the decision tree from CART. CART is the most flexible method, and no model has to be specified regarding presence of interactions and form of the relationship between outcome and predictor variables.

Localised transmission hotspots of a typhoid fever outbreak in the Democratic Republic of Congo.

INTRODUCTION: In a semi-urban setting in the Democratic Republic of Congo, this study aims to understand the dynamic of a typhoid fever (TF) outbreak and to assess: a) the existence of hot spots for TF transmission and b) the difference between typhoid cases identified within those hot spots and the general population in relation to socio-demographic characteristics, sanitation practice, and sources of drinking water. METHODS: This was a retrospective analysis of TF outbreaks in 2011 in Kikwit, DRC using microbiological analysis of water sources and a structured interview questionnaire. RESULTS: There were a total of 1430 reported TF cases. The outbreak's epidemic curve shows earliest and highest peak attack rates (AR) in three military camps located in Kikwit (Ebeya 3.2%; Ngubu 3.0%; and Nsinga 2.2%) compared to an average peak AR of 0.6% in other affected areas. A total 320 cases from the military camps and the high burden health areas were interviewed. Typhoid cases in the military camps shared a latrine with more than one family (P<0.02). All tap water sources in both the military camps and general population were found to be highly contaminated with faecal coliforms. CONCLUSION: The role of military camps in Kikwit as early hotspots of TF transmission was likely associated with lower sanitary and hygiene conditions. The proximity of camps to the general population might have been responsible for disseminating TF to the general population. Mapping of cases during an outbreak could be crucial to identify hot spots for transmission and institute corrective measures.

Localised transmission hotspots of a typhoid fever outbreak in the Democratic Republic of Congo

Introduction: in a semi-urban setting in the Democratic Republic of Congo, this study aims to understand the dynamic of a typhoid fever (TF) outbreak and to assess: a) the existence of hot spots for TF transmission and b) the difference between typhoid cases identified within those hot spots and the general population in relation to socio-demographic characteristics, sanitation practice, and sources of drinking water.Methods: this was a retrospective analysis of TF outbreaks in 2011 in Kikwit, DRC using microbiological analysis of water sources and a structured interview questionnaire.Results: there were a total of 1430 reported TF cases. The outbreak's epidemic curve shows earliest and highest peak attack rates (AR) in three military camps located in Kikwit (Ebeya 3.2%; Ngubu 3.0%; and Nsinga 2.2%) compared to an average peak AR of 0.6% in other affected areas. A total 320 cases from the military camps and the high burden health areas were interviewed. Typhoid cases in the military camps shared a latrine with more than one family (P<0.02). All tap water sources in both the military camps and general population were found to be highly contaminated with faecal coliforms.Conclusion: the role of military camps in Kikwit as early hotspots of TF transmission was likely associated with lower sanitary and hygiene conditions. The proximity of camps to the general population might have been responsible for disseminating TF to the general population. Mapping of cases during an outbreak could be crucial to identify hot spots for transmission and institute corrective measures

Organizing the Donation of Convalescent Plasma for a Therapeutic Clinical Trial on Ebola Virus Disease: The Experience in Guinea.

Although convalescent plasma (CP) transfusion was prioritized among potential Ebola treatments by the World Health Organization, there were concerns on the feasibility of its implementation. We report on the successful organization of donor mobilization and plasma collection as part of the Ebola-Tx clinical trial from November 2014 to July 2015 in Conakry, Guinea. Project implementation registers, tools and reports, mission reports, and minutes of research team meetings were used to reconstruct the sequence of events on how donor mobilization was organized, plasmapheresis was set up, and how effective this approach was in collecting CP. An initial needs assessment of the Guinean National Blood Transfusion Center resulted in targeted training of staff on site, resulting in autonomy and independent production of CP within 3 months. The Conakry Ebola Survivors Association played a direct role in donor mobilization and organization of CP donations. A total of 98 Ebola survivors were screened for plasma donation, of which 84 were found eligible for plasmapheresis. Of these, 26 (30.9%) were excluded. The remaining 58 donors made a total of 90 donations, corresponding to 50.9 L of CP. This sufficed to treat the 99 eligible patients enrolled in the trial. Within a poor resource emergency context, transfusion capacity could be rapidly improved through the strengthening of local capacities and gradual transfer of skills coupled with active involvement of Ebola survivors. However, large-scale plasma collection or multisite studies may require further adaptations of both strategy and logistics. The Ebola-Tx trial was funded by the European Union and others.

Performance of the PointCare NOW system for CD4 counting in HIV patients based on five independent evaluations

Introduction: Point-of-care (POC) CD4 testing can improve access to treatment by enabling decentralization and reducing patient loss-to-follow-up. As new POC CD4 technologies become available, their performance should be assessed before widespread deployment. This study reports the findings of five independent evaluations of the PointCare NOW CD4 system. Materials/methods: Evaluations were conducted in Southern Africa (Mozambique, South Africa) and North America (Canada, USA). 492 blood samples (55 from HIV-negative blood donors and 437 from HIV-infected patients, including 20 children aged between 12 and 59 months) were tested with both the PointCare NOW and reference flow cytometry instruments. Assessment of bias, precision and levels of clinical misclassification for absolute and percent CD4 count was conducted.

Prozone in malaria rapid diagnostics tests: how many cases are missed?

Background: Prozone means false-negative or false-low results in antigen-antibody reactions, due to an excess of either antigen or antibody. The present study prospectively assessed its frequency for malaria rapid diagnostic tests (RDTs) and Plasmodium falciparum samples in an endemic field setting. Methods: From January to April 2010, blood samples with P. falciparum high parasitaemia (≥ 4% red blood cells infected) were obtained from patients presenting at the Provincial Hospital of Tete (Mozambique). Samples were tested undiluted and 10-fold diluted in saline with a panel of RDTs and results were scored for line intensity (no line visible, faint, weak, medium and strong). Prozone was defined as a sample which showed no visible test line or a faint or weak test line when tested undiluted, and a visible test line of higher intensity when tested 10-fold diluted, as observed by two blinded observers and upon duplicate testing. Results: A total of 873/7,543 (11.6%) samples showed P. falciparum, 92 (10.5%) had high parasitaemia and 76 were available for prozone testing. None of the two Pf-pLDH RDTs, but all six HRP-2 RDTs showed prozone, at frequencies between 6.7% and 38.2%. Negative and faint HRP-2 lines accounted for four (3.8%) and 15 (14.4%) of the 104 prozone results in two RDT brands. For the most affected brand, the proportions of prozone with no visible or faint HRP-2 lines were 10.9% (CI: 5.34-19.08), 1.2% (CI: 0.55-2.10) and 0.1% (CI: 0.06-0.24) among samples with high parasitaemia, all positive samples and all submitted samples respectively. Prozone occurred mainly, but not exclusively, among young children. Conclusion: Prozone occurs at different frequency and intensity in HRP-2 RDTs and may decrease diagnostic accuracy in the most affected RDTs.