INTERVAL ESTIMATION OF TREATMENT EFFECTS IN DOUBLE CONSENT RANDOMIZED DESIGN

Abstract: The double consent randomized design, in which the physician and the patient know exactly what treatment the patient receives, has been proposed to alleviate the concern in carrying out a conventional randomized trial. In the latter, the assignment of patients to treatments after obtaining patients' informed consents depends completely on a chance mechanism. We develop four interval estimators, two using the delta method or the principle of Fieller's Theorem calculated over the pooled samples of eligible patients, and two calculated over the samples excluding patients who have treatment preference. Using Monte Carlo simulation, we evaluate and compare the performance of these estimators in a variety of situations. We note that the estimators using the principle of Fieller's Theorem outperform those derived from the delta method with respect to both coverage probability and average length in almost all situations considered here. We further note that when the expected number of patients who have no treatment preference is moderate or large (say ≥ 25) per treatment, the interval estimator using Fieller's Theorem calculated over the restricted samples is generally more efficient than those calculated over the entire pooled samples without much loss of accuracy as measured by coverage probability. On the other hand, when the expected number of patients who have no treatment preference is small, the coverage probability for the estimators calculated over the restricted samples tends to be less than the desired confidence level, while the coverage probability of the estimator using Fieller's Theorem on the pooled samples may still agree with the desired confidence level

Trends and Factors Associated with Initial and Recurrent Methicillin-Resistant (MRSA) Skin and Soft-Tissue Infections among HIV-Infected Persons

Background: Factors associated with initial methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections (SSTIs) and their recurrence have not been fully elucidated among HIV-infected persons. Methods: We retrospectively evaluated a large cohort of HIV-infected patients from 1993 to 2010 for culture-proven MRSA SSTIs. Separate logistic regression models evaluated factors associated with initial and recurrent infections. Results: Of the 794 patients, 63 (8%) developed an initial infection (19.8 infections/1000 person years [PY]); risk factors included CD4 count <500 cells/mm 3 and HIV RNA level ≥400 copies/mL ( P < .01), US Centers for Disease Control and Prevention (CDC) stage C versus A/B ( P < .01), and injection drug use (IDU, P < .01). In all, 27% developed recurrence (206 infections/1000 PY); risk factors included hospital admission ( P = .02). Minocycline for treatment of the initial infection was associated with an 80% decreased odds for recurrence ( P = .03). Conclusion: HIV control and avoidance of IDU may be useful in reducing rates of MRSA SSTIs among HIV-infected persons

Efficacy of an enhanced linkage to HIV care intervention at improving linkage to HIV care and achieving viral suppression following home-based HIV testing in rural Uganda: study protocol for the Ekkubo/PATH cluster randomized controlled trial

Abstract Background Though home-based human immunodeficiency virus (HIV) counseling and testing (HBHCT) is implemented in many sub-Saharan African countries as part of their HIV programs, linkage to HIV care remains a challenge. The purpose of this study is to test an intervention to enhance linkage to HIV care and improve HIV viral suppression among individuals testing HIV positive during HBHCT in rural Uganda. Methods The PATH (Providing Access To HIV Care)/Ekkubo Study is a cluster-randomized controlled trial which compares the efficacy of an enhanced linkage to HIV care intervention vs. standard-of-care (paper-based referrals) at achieving individual and population-level HIV viral suppression, and intermediate outcomes of linkage to care, receipt of opportunistic infection prophylaxis, and antiretroviral therapy initiation following HBHCT. Approximately 600 men and women aged 18-59 who test HIV positive during district-wide HBHCT in rural Uganda will be enrolled in this study. Villages (clusters) are pair matched by population size and then randomly assigned to the intervention or standard-of-care arm. Study teams visit households and participants complete a baseline questionnaire, receive HIV counseling and testing, and have blood drawn for HIV viral load and CD4 testing. At baseline, standard-of-care arm participants receive referrals to HIV care including a paper-based referral and then receive their CD4 results via home visit 2 weeks later. Intervention arm participants receive an intervention counseling session at baseline, up to three follow-up counseling sessions at home, and a booster session at the HIV clinic if they present for care. These sessions each last approximately 30 min and consist of counseling to help clients: identify and reduce barriers to HIV care engagement, disclose their HIV status, identify a treatment supporter, and overcome HIV-related stigma through links to social support resources in the community. Participants in both arms complete interviewer-administered questionnaires at six and 12 months follow-up, HIV viral load and CD4 testing at 12 months follow-up, and allow access to their medical records. Discussion The findings of this study can inform the integration of a potentially cost-effective approach to improving rates of linkage to care and HIV viral suppression in HBHCT. If effective, this intervention can improve treatment outcomes, reduce mortality, and through its effect on individual and population-level HIV viral load, and decrease HIV incidence. Trial registration NCT0254567

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes.

BACKGROUND:Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather. METHODOLOGY/PRINCIPAL FINDINGS:We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution. CONCLUSIONS/SIGNIFICANCE:Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning

Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes.

BackgroundDengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather.Methodology/principal findingsWe developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature &gt;22°C for 7+ weeks and minimum temperature &gt;14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity &gt;80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution.Conclusions/significanceLocal duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning

Comparison of dengue distribution by weather component across 6 high transmission locations in Peru.

<p>Left column: Annual frequency of weather interval per location is shown for each weather component. Grid interval is 1°C for temperature and 2% for humidity. Center column: distribution of cumulative incidence rates (1994–2012) across weather intervals for each location is shown for each weather component. Right column: Maximum dengue impact per weather interval is shown for each location, 1994–2012.</p

Profile of maximum dengue impact across Peru’s temperature-humidity weather-space.

<p>Upper panel represents all of Peru. Top row: Maximum dengue impact observed per weather interval is shown for all district-weeks across Peru, 2005–2015. Second row: The frequency distribution of weather intervals (where time is spent per week) annually is shown for all districts across Peru. Lower panel represents the 6 highest dengue incidence regions of Peru (Tumbes, Piura, Maynas, Alto Amazonas, Ucayali, Madre de Dios). Third row: Maximum dengue impact observed per weather interval is shown for all district-weeks across the 6 areas combined. Bottom row: The frequency distribution of weather intervals (where time is spent per week) annually is shown for all districts across the 6 highest dengue incidence locations. The shaded grey area indicates the weather-space for all of Peru. Grid interval is 1°C temperature and 2% humidity.</p

Relationship between weather and dengue incidence magnitude across districts.

<p>Top row: Annual temperature and humidity ranges are shown versus district incidence rates, 2005–2012. Mean weather ranges are shown for dengue-negative districts and by percentile groups in 5% increments for dengue-positive districts. P-values represent tests of association between weather range and incidence per district. Bottom row: Relationship between incidence and minimum annual duration above specific temperatures is shown in left/center panels. Bottom right: For mean temperature >25°C, as humidity rises from 60% to 80%, incidence rates accelerate in highest transmission areas, <i>p</i><0.00001.</p

Comparison of dengue distribution by weather component across 6 high transmission locations in Peru.

<p>Left column: Annual frequency of weather interval per location is shown for each weather component. Grid interval is 1°C for temperature and 2% for humidity. Center column: distribution of cumulative incidence rates (1994–2012) across weather intervals for each location is shown for each weather component. Right column: Maximum dengue impact per weather interval is shown for each location, 1994–2012.</p