Biology subjects

Williams, B. G.

Publications and source records attributed to Williams, B. G..

4 recordsLinked to original sources

bioRxiv2018

HIV-Attributed Causes of Death in the Medical Ward at the Chris Hani Baragwanath Hospital, South Africa

BackgroundThere are sparse data in Africa on the association between HIV infection and deaths from underlying medical conditions. Using records from the Chris Hani Baragwanath Hospital (CHBH) in Soweto, South Africa, we determined mortality from medical conditions associated with HIV.\n\nMethodsFrom January 2006 to December 2009 AB collected data on 15,725 deaths including age, sex, day of admittance and death, HIV status, ART initiation and CD4+ cell counts and reviewed the underlying cause of death using medical notes. Conditions known to be associated with HIV were cases; conditions not associated with HIV were controls. We calculate the HIV odds-ratios for cases relative to controls and HIV-attributable deaths as the fraction of those with each condition, the disease-attributable fraction (DA), and as the fraction of all deaths, the population-attributable fraction (PAF).\n\nInterpretationThe high prevalence of HIV among those that died in the medical wards at the CHBH, especially in those below the age of 50 years, demonstrates the impact of the HIV-epidemic on adult mortality and hospital services and the extent to which early antiretroviral treatment would have reduced the burden of both. Of the deaths included in the analysis the prevalence of HIV was 61% and the prevalence of AIDS related conditions was 69%. The HIV-attributable fraction was 36% in the whole sample and 60% in those that were HIV-positive. Cryptococcosis, Kaposis sarcoma and Pneumocystis jeroveci are highly predictive of HIV while TB, gastroenteritis and anaemia are very strongly associated with HIV. The greatest number of deaths attributable to HIV was among those dying of TB or of other respiratory conditions.\n\nFundingNo funding was received for this study.

epidemiology↗

bioRxiv2018

Ending AIDS: trends in the incidence of HIV in eastern and southern Africa

While great progress has been made in the control and management of the HIV epidemic there is still much to be done. Using trends in the rate of new HIV infections in eastern and southern Africa we assess the current state of the epidemic and evaluate the future prospects for controlling it. If we let an incidence of 1 per 1,000 people represent a control threshold then this has been reached, or will probably be reached by 2020, in eastern Africa and is reachable by 2020 in those southern African countries that do not have particularly strong social and economic ties to South Africa if they continue to scale up their treatment programmes. In South Africa and its immediate neighbours Lesotho, Mozambique and Swaziland, the prospects are less certain. These countries are unlikely to reach the control threshold by 2020 but with sufficient political will and commitment to treatment for all could do so by 2030.\n\nThere are two important caveats. First, reaching the control threshold still leaves 35 thousand new infections a year. As the lessons of polio remind us, finding the last few, hard to reach cases will demand more focussed strategies. Second, ending AIDS will not end HIV and about 35 million people will have to be kept on ART for the next 30 to 40 years unless and until a cure is discovered. Even if we assume a modest cost of, say, US$100 per person per year for ART treatment and support, this corresponds to a continuing financial commitment of US$3.5 Bn per year although this is substantially less than the approximately US$ 40 Bn per year currently committed to HIV and AIDS.

epidemiology↗

bioRxiv2017

Dynamics and Control of Infections on Social Networks of Population Types

Random mixing in host populations has been a convenient simplifying assumption in the study of epidemics, but neglects important differences in contact rates within and between population groups. For HIV/AIDS, the assumption of random mixing is inappropriate for epidemics that are concentrated in groups of people at high risk, including female sex workers (FSW) and their male clients (MCF), injecting drug users (IDU) and men who have sex with men (MSM). To find out who transmits infection to whom and how that affects the spread and containment of infection remains a major empirical challenge in the epidemiology of HIV/AIDS. Here we develop a technique, based on the routine sampling of infection in linked population groups (a social network of population types), which shows how an HIV/AIDS epidemic in Can Tho Province of Vietnam began in FSW, was propagated mainly by IDU, and ultimately generated most cases among the female partners of MCF (FPM). Calculation of the case reproduction numbers within and between groups, and for the whole network, provides insights into control that cannot be deduced simply from observations on the prevalence of infection. Specifically, the per capita rate of HIV transmission was highest from FSW to MCF, and most HIV infections occurred in FPM, but the number of infections in the whole network is best reduced by interrupting transmission to and from IDU. This analysis can be used to guide HIV/AIDS interventions using needle and syringe exchange, condom distribution and antiretroviral therapy. The method requires only routine data and could be applied to infections in other populations.

epidemiology↗

bioRxiv2017

90-90-90, epidemic control, and ending AIDS: review of global situation and recommendations

HIV remains a devastating pandemic HIV remains a devastating... Ending AIDS The prevention vs. treatment... Economics of ending AIDS Major innovations accelerating... HIV self-tests Universal treatment regimen Comprehensive community-based... Standardized M and E... Unification of global leadership... Last mile strategies,... Conclusion References Although human immunodeficiency virus (HIV) first came to our attention thirty-seven years ago, the acquired immunodeficiency syndrome (AIDS) which it causes is, without treatment, 100% fatal with devastating consequences for millions of people1. More than 35 million people have already died of ...

epidemiology↗