Suchergebnisse

BackgroundDolutegravir (DTG) is a once-daily unboosted second-generation integrase-inhibitor that along with two nucleoside reverse transcriptase inhibitors is one of several regimens recommended by the United States, United Kingdom and European Union for first-line antiretroviral treatment of people with HIV infection. Our objective was to review the evidence for the efficacy and safety of DTG-based first-line regimens compared to efavirenz (EFV)-based regimens.MethodsWe conducted a systematic review. We comprehensively searched a range of databases as well as conference abstracts and a trials registry. We used Cochrane methods in screening and data collection and assessed each study's risk of bias with the Cochrane tool. We meta-analyzed data using a fixed-effects model. We used GRADE to assess evidence quality.ResultsFrom 492 search results, we identified two randomized controlled trials, reported in five peer-reviewed articles and one conference abstract. One trial tested two DTG-based regimens (DTG + abacavir (ABC) + lamivudine (3TC) or DTG + tenofovir + emtricitabine) against an EFV-based regimen (EFV+ ABC+3TC). The other trial tested DTG+ABC+3TC against EFV+ABC+3TC. In meta-analysis, DTG-containing regimens were superior to EFV-containing regimens at 48 weeks and at 96 weeks (RR = 1.10, 95% CI 1.04-1.16; and RR = 1.12, 95% CI 1.04-1.21, respectively). In one trial, the DTG-containing regimen was superior at 144 weeks (RR = 1.13, 95% CI 1.02-1.24). DTG-containing regimens were superior in reducing treatment discontinuation compared to those containing EFV at 96 weeks and at 144 weeks (RR = 0.27, 95% CI 0.15-0.50; and RR = 0.28, 95% CI 0.16-0.48, respectively). Risk of serious adverse events was similar in each regimen at 96 weeks (RR = 1.15, 95% CI 0.80-1.63) and 144 weeks (RR = 0.93, 95% CI 0.68-1.29). Risk of bias was moderate overall, as was GRADE evidence quality.ConclusionsDTG-based regimens should be considered in future World Health Organization guidelines for initial HIV treatment.

The acquired immunodeficiency syndrome (AIDS) was first described as a disease of homosexual men. The first cases of AIDS in children were reported in 1982 and involved a transfusion recipient and four infants born to women at increased risk for AIDS. Infants may acquire their infection perinatally or possibly postnatally through infected breast milk. Parenterally acquired infection, through transfusion of blood or blood products, occurs in infants, children, and adolescents. Adolescents are also at risk for infection through sexual transmission and through shared needles among intravenous drug users. By January 1987, 1.4% of the AIDS cases were in children less than 13 years old, and 0.4% were in adolescents 13 to 19 years old. Additionally, 4.4% of the total AIDS cases were reported in 20 to 24 year olds, which most likely reflects infection which occured during adolescence. In children less than 13 years old, infection occurred primarily thorugh perinatal transmission from mothers who were intravenous drug users or sexual partners of intravenous drug users. Adolescent cases of AIDS have followed adult patterns of transmission with most cases resulting from sexual transmission. As the prevalence of infection with the human immunodeficiency virus increases, increases in drug-use-associated transmission in women followed by perinatal transmission to infants and sexual transmission in adolescents seems likely to occur. To prevent further spread, health agencies must develop and target extensive AIDS prevention campaigns at adolescents, young adults, and sexually active women.

BackgroundApproximately one in every five adolescent girls in Kenya has either had a live birth or is pregnant with her first child. There is an urgent need to understand the language and symbols used to represent adolescent pregnancy, if the current trend in adolescent pregnancy is to be reversed. Agreement on the definition of a societal problem is an important precursor to a social issue's political prioritization and priority setting.MethodsWe apply the Public Arenas Model to appraise the environments, definitions, competition dynamics, principles of selection and current actors involved in problem-solving and prioritizing adolescent pregnancy as a policy issue. Using a focused ethnographic approach, we undertook semi-structured interviews with 14 members of adolescent sexual reproductive health networks at the national level and conducted thematic analysis of the interviews.FindingsWe found that existing definitions center around adolescent pregnancy as a "disease" that needs prevention and treatment, socially deviant behaviour that requires individual agency, and a national social concern that drains public resources and therefore needs to be regulated. These competing definitions contribute to the rarity of the topic achieving traction within the political agenda and contribute to conflicting solutions, such as lowering the legal age of consenting to sex, while limiting access to contraceptive information and services to minors.ConclusionThis paper provides a timely theoretical approach to draw attention to the different competing definitions and subsequent divergent interpretations of the problem of adolescent pregnancy in Kenya. Adolescent reproductive health stakeholders need to be familiar with the existing definitions and deliberately reframe this important social problem for better political prioritization and resource allocation. We recommend a definition of adolescent pregnancy that cuts across different arenas, and leverages already existing dominant and concurrent social and economic issues that are already on the agenda table.

BackgroundDespite the high burden of adverse adolescent sexual and reproductive health (SRH) outcomes, it has remained a low political priority in Kenya. We examined factors that have shaped the lack of current political prioritization of adolescent SRH service provision.MethodsWe used the Shiffman and Smith policy framework consisting of four categories-actor power, ideas, political contexts, and issue characteristics-to analyse factors that have shaped political prioritization of adolescent SRH. We undertook semi-structured interviews with 14 members of adolescent SRH networks between February and April 2019 at the national level and conducted thematic analysis of the interviews.FindingsSeveral factors hinder the attainment of political priority for adolescent SRH in Kenya. On actor power, the adolescent SRH community was diverse and united in adoption of international norms and policies, but lacked policy entrepreneurs to provide strong leadership, and policy windows were often missed. Regarding ideas, community members lacked consensus on a cohesive public positioning of the problem. On issue characteristics, the perception of adolescents as lacking political power made politicians reluctant to act on the existing data on the severity of adolescent SRH. There was also a lack of consensus on the nature of interventions to be implemented. Pertaining to political contexts, sectoral funding by donors and government treasury brought about tension within the different government ministries resulting in siloed approaches, lack of coordination and overall inefficiency. However, the SRH community has several strengths that augur well for future political support. These include the diverse multi-sectoral background of its members, commitment to improving adolescent SRH, and the potential to link with other health priorities such as maternal health and HIV/AIDS.ConclusionIn order to increase political attention to adolescent SRH in Kenya, there is an urgent need for policy actors to: 1) create a more cohesive community of advocates across sectors, 2) develop a clearer public positioning of adolescent SRH, 3) agree on a set of precise approaches that will resonate with the political system, and 4) identify and nurture policy entrepreneurs to facilitate the coupling of adolescent SRH with potential solutions when windows of opportunity arise.

BackgroundDespite the high burden of adverse adolescent sexual and reproductive health (SRH) outcomes, it has remained a low political priority in Kenya. We examined factors that have shaped the lack of current political prioritization of adolescent SRH service provision.MethodsWe used the Shiffman and Smith policy framework consisting of four categories-actor power, ideas, political contexts, and issue characteristics-to analyse factors that have shaped political prioritization of adolescent SRH. We undertook semi-structured interviews with 14 members of adolescent SRH networks between February and April 2019 at the national level and conducted thematic analysis of the interviews.FindingsSeveral factors hinder the attainment of political priority for adolescent SRH in Kenya. On actor power, the adolescent SRH community was diverse and united in adoption of international norms and policies, but lacked policy entrepreneurs to provide strong leadership, and policy windows were often missed. Regarding ideas, community members lacked consensus on a cohesive public positioning of the problem. On issue characteristics, the perception of adolescents as lacking political power made politicians reluctant to act on the existing data on the severity of adolescent SRH. There was also a lack of consensus on the nature of interventions to be implemented. Pertaining to political contexts, sectoral funding by donors and government treasury brought about tension within the different government ministries resulting in siloed approaches, lack of coordination and overall inefficiency. However, the SRH community has several strengths that augur well for future political support. These include the diverse multi-sectoral background of its members, commitment to improving adolescent SRH, and the potential to link with other health priorities such as maternal health and HIV/AIDS.ConclusionIn order to increase political attention to adolescent SRH in Kenya, there is an urgent need for policy actors to: 1) create a more cohesive community ...

Background: Private healthcare providers deliver a significant proportion of healthcare services in low- and middle-income countries (LMIC). Poorer patients get sick and go without care more frequently, and spend more of their incomes on private healthcare than the wealthy. This review is focused on comparing health outcomes in private versus public care settings. It seeks to summarize what is known regarding the relative morbidity or mortality outcomes that result from treatment by public or private providers in LMIC.Methods: We conducted a systematic review of studies evaluating the impact of public and private healthcare provision. We performed meta-analyses on data within identified studies, in order to estimate the effects of type of healthcare provision on identified health outcomes.Results: Twenty-one studies met our inclusion criteria and explicitly compared health outcomes between the public and private sectors. Of those, 17 were cohortstudies, from 9 countries. Eleven studies were conducted in lower-middle-incomecountries ($996–$3,945 GNI per capita) and 10 studies from upper-middle-incomecountries ($3,946–$12,195 GNI per capita). Eighteen studies were conducted inurban settings. Fifteen of the 21 studies provided mortality for a health outcome,and studies examined a wide range of diseases, with tuberculosis (TB) being themost represented. A meta-analysis of all studies exploring the impact of healthcare type and mortality showed that patients in a private healthcare setting are less likely to die than patients in a public healthcare setting (OR 0.60; 95% CI 0.41–0.88). The pooled analysis showed that patients in a private healthcare facility are more likely to have unsuccessfully completed TB treatment than patients in a public healthcare facility (OR 2.04; 95% CI 1.07–3.89). Regardless of outcomes, the quality of evidence is rated, by objective measures, as either low or very low. Conclusions: More evidence is needed to compare health outcomes between the public and private sectors. Governments and researchers can play a critical role in improving the evidence base for decision making about the contributions of the public andprivate sectors in a given country's health system.Governments should encourage data collection in both public and private settings that would permit ongoing comparison of clinical data. When government facilities are absent or insufficient, contracting with private-sector facilities or providerswould appear to be an acceptable option. Governments must consider appropriateprofit margins, regulations and training for private providers.Further research is needed in this area, and should include low-income countriesand rural settings. Diseases of the poor – notably malaria and childhood illnesses – are largely absent from the current literature, with the exception of one study onHIV/AIDS and six on TB.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all ...

BackgroundClinical sequelae of Ebola virus disease (EVD) have not been described more than 3 years postoutbreak. We examined survivors and close contacts from the 1995 Ebola outbreak in Kikwit, Democratic Republic of Congo (DRC), and determined prevalence of abnormal neurological, cognitive, and psychological findings and their association with EVD survivorship.MethodsFrom August to September 2017, we conducted a cross-sectional study in Kikwit, DRC. Over 2 decades after the EVD outbreak, we recruited EVD survivors and close contacts from the outbreak to undergo physical examination and culturally adapted versions of the Folstein mini-mental status exam (MMSE) and Goldberg anxiety and depression scale (GADS). We estimated the strength of relationships between EVD survivorship and health outcomes using linear regression models by comparing survivors versus close contacts, adjusting for age, sex, educational level, marital status, and healthcare worker status.ResultsWe enrolled 20 EVD survivors and 187 close contacts. Among the 20 EVD survivors, 4 (20%) reported at least 1 abnormal neurological symptom, and 3 (15%) had an abnormal neurological examination. Among the 187 close contacts, 14 (11%) reported at least 1 abnormal neurologic symptom, and 9 (5%) had an abnormal neurological examination. EVD survivors had lower mean MMSE and higher mean GADS scores as compared to close contacts (MMSE: adjusted coefficient: -1.85; 95% confidence interval [CI]: -3.63, -0.07; GADS: adjusted coefficient: 3.91; 95% CI: 1.76, 6.04).ConclusionsEVD survivors can have lower cognitive scores and more symptoms of depression and anxiety than close contacts more than 2 decades after Ebola virus outbreaks.

BackgroundOur understanding of the different effects of targeted versus nontargeted violence on Ebola virus (EBOV) transmission in Democratic Republic of the Congo (DRC) is limited.MethodsWe used time-series data of case counts to compare individuals in Ebola-affected health zones in DRC, April 2018-August 2019. Exposure was number of violent events per health zone, categorized into Ebola-targeted or Ebola-untargeted, and into civilian-induced, (para)military/political, or protests. Outcome was estimated daily reproduction number (Rt) by health zone. We fit linear time-series regression to model the relationship.ResultsAverage Rt was 1.06 (95% confidence interval [CI], 1.02-1.11). A mean of 2.92 violent events resulted in cumulative absolute increase in Rt of 0.10 (95% CI, .05-.15). More violent events increased EBOV transmission (P = .03). Considering violent events in the 95th percentile over a 21-day interval and its relative impact on Rt, Ebola-targeted events corresponded to Rt of 1.52 (95% CI, 1.30-1.74), while civilian-induced events corresponded to Rt of 1.43 (95% CI, 1.21-1.35). Untargeted events corresponded to Rt of 1.18 (95% CI, 1.02-1.35); among these, militia/political or ville morte events increased transmission.ConclusionsEbola-targeted violence, primarily driven by civilian-induced events, had the largest impact on EBOV transmission.

BackgroundOur understanding of the different effects of targeted versus nontargeted violence on Ebola virus (EBOV) transmission in Democratic Republic of the Congo (DRC) is limited.MethodsWe used time-series data of case counts to compare individuals in Ebola-affected health zones in DRC, April 2018-August 2019. Exposure was number of violent events per health zone, categorized into Ebola-targeted or Ebola-untargeted, and into civilian-induced, (para)military/political, or protests. Outcome was estimated daily reproduction number (Rt) by health zone. We fit linear time-series regression to model the relationship.ResultsAverage Rt was 1.06 (95% confidence interval [CI], 1.02-1.11). A mean of 2.92 violent events resulted in cumulative absolute increase in Rt of 0.10 (95% CI, .05-.15). More violent events increased EBOV transmission (P = .03). Considering violent events in the 95th percentile over a 21-day interval and its relative impact on Rt, Ebola-targeted events corresponded to Rt of 1.52 (95% CI, 1.30-1.74), while civilian-induced events corresponded to Rt of 1.43 (95% CI, 1.21-1.35). Untargeted events corresponded to Rt of 1.18 (95% CI, 1.02-1.35); among these, militia/political or ville morte events increased transmission.ConclusionsEbola-targeted violence, primarily driven by civilian-induced events, had the largest impact on EBOV transmission.

As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes point processes to model the expected cumulative case count using daily case counts from May 3, 2018, to June 16, 2019, initially reported by the Ministry of Health of DRC and later confirmed in World Health Organization situation reports. We generated probabilistic estimates of the ongoing EVD outbreak in DRC extending both before and after June 16, 2019, and evaluated their accuracy by comparing forecasted vs. actual outbreak sizes, out-of-sample log-likelihood scores and the error per day in the median forecast. The median estimated outbreak sizes for the prospective thee-, six-, and nine-week projections made using data up to June 16, 2019, were, respectively, 2317 (95% PI: 2222, 2464); 2440 (95% PI: 2250, 2790); and 2544 (95% PI: 2273, 3205). The nine-week projection experienced some degradation with a daily error in the median forecast of 6.73 cases, while the six- and three-week projections were more reliable, with corresponding errors of 4.96 and 4.85 cases per day, respectively. Our findings suggest the Hawkes point process may serve as an easily-applied statistical model to predict EVD outbreak trajectories in near real-time to better inform decision-making and resource allocation during Ebola response efforts.