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Background COVID-19 mitigation strategies have been challenging to implement in resource-limited settings such as Malawi due to the potential for widespread disruption to social and economic well-being. Here we estimate the clinical severity of COVID-19 in Malawi, quantifying the potential impact of intervention strategies and increases in health system capacity. Methods The infection fatality ratios (IFR) in Malawi were estimated by adjusting reported IFR for China accounting for demography, the current prevalence of comorbidities and health system capacity. These estimates were input into an age-structured deterministic model, which simulated the epidemic trajectory with non-pharmaceutical interventions. The impact of a novel therapeutic agent and increases in hospital capacity and oxygen availability were explored, given different assumptions on mortality rates. Findings The estimated age-specific IFR in Malawi are higher than those reported for China, however the younger average age of the population results in a slightly lower population-weighted IFR (0.48%, 95% uncertainty interval [UI] 0.30% – 0.72% compared with 0.60%, 95% CI 0.4% – 1.3% in China). The current interventions implemented, (i.e. social distancing, workplace closures and public transport restrictions) could potentially avert 3,100 deaths (95% UI 1,500 – 4,500) over the course of the epidemic. Enhanced shielding of people aged ≥ 60 years could avert a further 30,500 deaths (95% UI 17,500 – 45,600) and halve ICU admissions at the peak of the outbreak. Coverage of face coverings of 60% under the assumption of 50% efficacy could be sufficient to control the epidemic. A novel therapeutic agent, which reduces mortality by 0.65 and 0.8 for severe and critical cases respectively, in combination with increasing hospital capacity could reduce projected mortality to 2.55 deaths per 1,000 population (95% UI 1.58 – 3.84). Conclusion The risks due to COVID-19 vary across settings and are influenced by age, underlying health and health system capacity.

Several SARS-CoV-2 vaccine candidates are now in late-stage trials, with efficacy and safety results expected by the end of 2020. Even under optimistic scenarios for manufacture and delivery, the doses available in 2021 are likely to be limited. Here we identify optimal vaccine allocation strategies within and between countries to maximise health (avert deaths) under constraints on dose supply. We extended an existing mathematical model of SARS-CoV-2 transmission across different country settings to model the public health impact of potential vaccines, using a range of target product profiles developed by the World Health Organization. We show that as supply increases, vaccines that reduce or block infection – and thus transmission – in addition to preventing disease have a greater impact than those that prevent disease alone, due to the indirect protection provided to high-risk groups. We further demonstrate that the health impact of vaccination will depend on the cumulative infection incidence in the population when vaccination begins, the duration of any naturally acquired immunity, the likely trajectory of the epidemic in 2021 and the level of healthcare available to effectively treat those with disease. Within a country, we find that for a limited supply (doses for

Background: Emerging evidence suggests ethnic minorities are disproportionatelyaffected by COVID-19. Detailed clinical analyses of multi-cultural hospitalized patientcohorts remain largely undescribed.Methods: We performed regression, survival andcumulative competing risk analyses to evaluate factors associated with mortality inpatients admitted for COVID-19 in three large London hospitals between February 25and April 5, censored as of May 1, 2020.Results: Of 614 patients (median age 69years, (IQR 25) and 62% male), 381 (62%) had been discharged alive, 178 (29%)died and 55 (9%) remained hospitalized at censoring. Severe hypoxemia (aOR 4.25,95%CI 2.36-7.64), leukocytosis (aOR 2.35, 95%CI 1.35-4.11), thrombocytopenia (aOR1.01, 95%CI 1.00-1.01, increase per 10x9decrease), severe renal impairment (aOR5.14, 95%CI 2.65-9.97), and low albumin (aOR 1.06, 95%CI 1.02-1.09, increase per gdecrease) were associated with death. Forty percent (244) were from black, Asian andother minority ethnic (BAME) groups, 38% (235) white and for 22% (135) ethnicity wasunknown. BAME patients were younger and had fewer comorbidities. Whilst theunadjusted odds of death did not differ by ethnicity, when adjusting for age, sex andcomorbidities, black patients were at higher odds of death compared to whites (aOR1.69, 95%CI 1.00-2.86). This association was stronger when further adjusting foradmission severity (aOR 1.85 95% CI 1.06-3.24). Conclusions: BAME patients were over-represented in our cohort and, whenaccounting for demographic and clinical profile of admission, black patients were atincreased odds of death. Further research is needed into biologic drivers of differencesin COVID-19 outcomes by ethnicity.

There were 189,403 deaths from any cause reported in England from 29th February to 5th June 2020 inclusive, and 11,278 all-cause deaths in Wales over the same period. Of those deaths, 44,736 (23.6%) registered COVID-19 on the death certificate in England, and 2,294 (20.3%) in Wales, while 144,667 (76.4%) were not recorded as having been due to COVID-19 in England, and 8,984 (79.7%) in Wales. However, it could be that some of the ‘non-COVID-19’ deaths have in fact also been caused by COVID-19, either as the direct cause of death, or indirectly through provisions for the pandemic impeding access to care for other conditions. There is uncertainty in how many of the non-COVID-19 deaths were directly or indirectly caused by the pandemic. We estimated the excess deaths that were not recorded as associated with COVID-19 in the death certificate (excess non-COVID-19 deaths) as the deaths for which COVID-19 was not reported as the cause, compared to those we would have expected to occur had the pandemic not happened. Expected deaths were forecast with an analysis of historic trends in deaths between 2010 and April 2020 using data by the Office of National Statistics and a statistical time series model. According to the model, we expected 136,294 (95% CI 133,882 - 138,696) deaths in England, and 8,983 (CI 8,051 - 9,904) in Wales over this period, significantly fewer than the number of deaths reported. This means that there were 8,983 (95% CI 5,971 - 10,785) total excess non-COVID-19 deaths in England. For every 100 COVID-19 deaths during the period from 29th February to 5th June 2020 there were 19 (95% CI 13 – 24) cumulative excess non-COVID-19 deaths. The proportion of cumulative excess non-COVID-19 deaths of all reported deaths during this period was 4.4% (95% CI 3.2% - 5.7%) in England, with small regional variations. Excess deaths were highest in the South East at 2,213 (95% CI 327 - 4,047) and in London at 1,937 (95% CI 896 - 3,010), respectively. There is no evidence of non-COVID-19 excess deaths in Wales. Excess non-COVID-19 deaths are occurring in individuals aged 85+ and 75-84, and those aged 45-64. For those aged 85+, excess non-COVID-19 deaths are driven by females, with 6,115 (95% CI 206 – 11,795) deaths in total but no significant findings for males of those ages. For ages 75-84, excess non-COVID-19 deaths are nearly double for females at 2,070 (95% CI 393 – 3,887) than for males at 1,336 (95% CI 938 – 1,710), while for ages 45-64, excess non-COVID-19 deaths for females are at 347 (95% CI 90 – 603), almost half those of males at 681 (95% CI 282 – 1,091). There is no evidence of excess non-COVID-19 deaths for ages 65-74, and those below 45. Excess non-COVID-19 deaths could be due to non-reporting of COVID-19 on the death certificate or an increase in mortality for non-COVID-19 conditions. Severely ill patients may have been unable to access life-saving emergency treatment because of constraints in healthcare provision, or because they avoided seeking care due to concern over hospital-acquired infection, or to avoid burdening healthcare providers. Further research into reasons for excess non-COVID-19 deaths is warranted. This report accompanies the weekly update of excess death estimates on the Github website of the Abdul Latif Jameel Institute of Disease and Emergency Analytics (J-IDEA) (https://j-idea.github.io/ONSdeaths/) which has been set up to be regularly updated until June 2022.

Background: COVID-19 has the potential to cause substantial disruptions to health services, including by cases overburdening the health system or response measures limiting usual programmatic activities. We aimed to quantify the extent to which disruptions in services for human immunodeficiency virus (HIV), tuberculosis (TB) and malaria in low- and middle-income countries with high burdens of those disease could lead to additional loss of life. Methods: We constructed plausible scenarios for the disruptions that could be incurred during the COVID-19 pandemic and used established transmission models for each disease to estimate the additional impact on health that could be caused in selected settings. Findings: In high burden settings, HIV-, TB- and malaria-related deaths over five years may increase by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 pandemic. We estimate the greatest impact on HIV to be from interruption to antiretroviral therapy, which may occur during a period of high health system demand. For TB, we estimate the greatest impact is from reductions in timely diagnosis and treatment of new cases, which may result from any prolonged period of COVID-19 suppression interventions. We estimate that the greatest impact on malaria burden could come from interruption of planned net campaigns. These disruptions could lead to loss of life-years over five years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV/TB epidemics. Interpretation: Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 pandemic. Funding: Bill & Melinda Gates Foundation, The Wellcome Trust, DFID, MRC

our estimates show that the percentage of individuals that have been infected is 4.1% [3.7%-4.5%], with wide variation between states. For all states, even for the worst affected states, we estimate that less than a quarter of the population has been infected; in New York, for example, we estimate that 16.6% [12.8%-21.6%] of individuals have been infected to date. Our attack rates for New York are in line with those from recent serological studies [1] broadly supporting our choice of infection fatality rate. There is variation in the initial reproduction number, which is likely due to a range of factors; we find a strong association between the initial reproduction number with both population density (measured at the state level) and the chronological date when 10 cumulative deaths occurred (a crude estimate of the date of locally sustained transmission). Our estimates suggest that the epidemic is not under control in much of the US: as of 17 May 2020 the reproduction number is above the critical threshold (1.0) in 24 [95% CI: 20-30] states. Higher reproduction numbers are geographically clustered in the South and Midwest, where epidemics are still developing, while we estimate lower reproduction numbers in states that have already suffered high COVID-19 mortality (such as the Northeast). These estimates suggest that caution must be taken in loosening current restrictions if effective additional measures are not put in place. We predict that increased mobility following relaxation of social distancing will lead to resurgence of transmission, keeping all else constant. We predict that deaths over the next two-month period could exceed current cumulative deaths by greater than two-fold, if the relationship between mobility and transmission remains unchanged. Our results suggest that factors modulating transmission such as rapid testing, contact tracing and behavioural precautions are crucial to offset the rise of transmission associated with loosening of social distancing. Overall, we show that while all US states have substantially reduced their reproduction numbers, there is little evidence that any states are approaching herd immunity and thus the epidemic is close to over in any state.

The impact of the COVID-19 pandemic in low-income settings is likely to be more severe due to limited healthcare capacity. Within these settings, however, there exists unfair or avoidable differences in health among different groups in society – health inequities – that mean that some groups are particularly at risk from the negative direct and indirect consequences of COVID-19. The structural determinants of these are often reflected in differences by income strata, with the poorest populations having limited access to preventative measures such as handwashing. Their more fragile income status will also mean that they are likely to be employed in occupations that are not amenable to social-distancing measures, thereby further reducing their ability to protect themselves from infection. Furthermore, these populations may also lack access to timely healthcare on becoming ill. We explore these relationships by using large-scale household surveys to quantify the differences in handwashing access, occupation and hospital access with respect to wealth status in low-income settings. We use a COVID-19 transmission model to demonstrate the impact of these differences. Our results demonstrate clear trends that the probability of death from COVID-19 increases with increasing poverty. On average, we estimate a 32.0% (2.5th-97.5th centile 8.0%-72.5%) increase in the probability of death in the poorest quintile compared to the wealthiest quintile from these three factors alone. We further explore how risk mediators and the indirect impacts of COVID-19 may also hit these same disadvantaged and vulnerable the hardest. We find that larger, inter-generational households that may hamper efforts to protect the elderly if social distancing are associated with lower-income countries and, within LMICs, lower wealth status. Poorer populations are also more susceptible to food security issues - with these populations having the highest levels under-nourishment whilst also being most dependent on their own food production. We show that timing of the COVID-19 epidemic in low-resource settings has the potential to interrupt planting and harvesting seasons for staple crops, thereby accentuating this vulnerability. These enhanced risks and key vulnerabilities – alongside the broader concerns surrounding displaced or conflict-affected populations - demonstrate the challenges that the most marginalised populations face during the ongoing COVID-19 pandemic.

COVID-19 has the potential to cause disruptions to health services in different ways; through the health system becoming overwhelmed with COVID-19 patients, through the intervention used to slow transmission of COVID-19 inhibiting access to preventative interventions and services, and through supplies of medicine being interrupted. We aim to quantify the extent to which such disruptions in services for HIV, TB and malaria in high burden low- and middle-income countries could lead to additional loss of life. In high burden settings, HIV, TB and malaria related deaths over 5 years may be increased by up to 10%, 20% and 36%, respectively, compared to if there were no COVID-19 epidemic. We estimate the greatest impact on HIV to be from interruption to ART, which may occur during a period of high or extremely high health system demand; for TB, we estimate the greatest impact is from reductions in timely diagnosis and treatment of new cases, which may result from a long period of COVID-19 suppression interventions; for malaria, we estimate that the greatest impact could come from reduced prevention activities including interruption of planned net campaigns, through all phases of the COVID-19 epidemic. In high burden settings, the impact of each type of disruption could be significant and lead to a loss of life-years over five years that is of the same order of magnitude as the direct impact from COVID-19 in places with a high burden of malaria and large HIV/TB epidemics. Maintaining the most critical prevention activities and healthcare services for HIV, TB and malaria could significantly reduce the overall impact of the COVID-19 epidemic.

Clinical characteristics and determinants of outcomes for hospitalised COVID-19 patients in the UK remain largely undescribed and emerging evidence suggests ethnic minorities might be disproportionately affected. We describe the characteristics and outcomes of patients hospitalised for COVID-19 in three large London hospitals with a multi-ethnic catchment population. We performed a retrospective cohort study on all patients hospitalised with laboratory-confirmed SARS-CoV-2 infection at Imperial College Healthcare NHS Trust between February 25 and April 5, 2020. Outcomes were recorded as of April 19, 2020. Logistic regression models, survival analyses and cumulative competing risk analyses were performed to evaluate factors associated with COVID-19 hospital mortality. Of 520 patients in this cohort (median age 67 years, (IQR 26) and 62% male), 302 (68%) had been discharged alive, 144 (32%) died and 74 (14%) were still hospitalised at the time of censoring. Increasing age (adjusted odds ratio [aOR] 2·16, 95%CI 1·50-3·12), severe hypoxia (aOR 3·75, 95%CI 1·80-7·80), low platelets (aOR 0·65, 95%CI 0.49·0·85), reduced estimated glomerular filtration rate (aOR 4·11, 95%CI 1·58-10·69), bilirubin >21mmol/L (aOR 2·32, 95%CI 1·05-5·14) and low albumin (aOR 0·77, 9%%CI 0·59-1·01) were associated with increased risk of in-hospital mortality. Individual comorbidities were not independently associated with risk of death. Regarding ethnicity, 209 (40%) were from a black and Asian minority, for 115 (22%) ethnicity was unknown and 196 (38%) patients were white. Compared to the latter, black patients were significantly younger and had less comorbidities. Whilst the crude OR of death of black compared to white patients was not significant (1·14, 95%CI 0·69-1·88, p=0.62), adjusting for age and comorbidity showed a trend towards significance (aOR 1·72, 95%CI 0·98-3·02, p=0.06) and further accounting for admission severity (Early Warning Score) showed a significant difference (aOR 1·83 95% CI 1·02-3·30, p=0.04). In the first study to describe the characteristics and predictors of outcome for hospitalised COVID-19 patients in the UK, we find that older age, male sex and admission hypoxia, thrombocytopenia, renal failure, hypoalbuminaemia and raised bilirubin are associated with increased odds of death. Ethnic minority groups were over-represented in our cohort and, compared to whites, people of black ethnicity may be at increased odds of mortality. Further research is urgently needed to investigate these associations on a larger scale.

The numbers of deaths caused by HIV could increase substantially if the COVID-19 epidemic leads to interruptions in the availability of HIV services. We compare publicly available scenarios for COVID-19 mortality with predicted additional HIV-related mortality based on assumptions about possible interruptions in HIV programs. An interruption in the supply of ART for 40% of those on ART for 3 months could cause a number of deaths on the same order of magnitude as the number that are anticipated to be saved from COVID-19 through social distancing measures. In contrast, if the disruption can be managed such that the supply and usage of ART is maintained, the increase in AIDS deaths would be limited to 1% over five years, although this could still be accompanied by substantial increases in new HIV infections if there are reductions in VMMC, oral PrEP use, and condom availability.

The World Health Organization has called for increased molecular testing in response to the COVID-19 pandemic, but different countries have taken very different approaches. We used a simple mathematical model to investigate the potential effectiveness of alternative testing strategies for COVID-19 control. Weekly screening of healthcare workers (HCWs) and other at-risk groups using PCR or point-of-care tests for infection irrespective of symptoms is estimated to reduce their contribution to transmission by 25-33%, on top of reductions achieved by self-isolation following symptoms. Widespread PCR testing in the general population is unlikely to limit transmission more than contact-tracing and quarantine based on symptoms alone, but could allow earlier release of contacts from quarantine. Immunity passports based on tests for antibody or infection could support return to work but face significant technical, legal and ethical challenges. Testing is essential for pandemic surveillance but its direct contribution to the prevention of transmission is likely to be limited to patients, HCWs and other high-risk groups.

Following the emergence of a novel coronavirus (SARS-CoV-2) and its spread outside of China, Europe is now experiencing large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions including case isolation, the closure of schools and universities, banning of mass gatherings and/or public events, and most recently, widescale social distancing including local and national lockdowns. In this report, we use a semi-mechanistic Bayesian hierarchical model to attempt to infer the impact of these interventions across 11 European countries. Our methods assume that changes in the reproductive number – a measure of transmission - are an immediate response to these interventions being implemented rather than broader gradual changes in behaviour. Our model estimates these changes by calculating backwards from the deaths observed over time to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. One of the key assumptions of the model is that each intervention has the same effect on the reproduction number across countries and over time. This allows us to leverage a greater amount of data across Europe to estimate these effects. It also means that our results are driven strongly by the data from countries with more advanced epidemics, and earlier interventions, such as Italy and Spain. We find that the slowing growth in daily reported deaths in Italy is consistent with a significant impact of interventions implemented several weeks earlier. In Italy, we estimate that the effective reproduction number, Rt, dropped to close to 1 around the time of lockdown (11th March), although with a high level of uncertainty. Overall, we estimate that countries have managed to reduce their reproduction number. Our estimates have wide credible intervals and contain 1 for countries that have implemented all interventions considered in our analysis. This means that the reproduction number may be above or below this value. With current interventions remaining in place to at least the end of March, we estimate that interventions across all 11 countries will have averted 59,000 deaths up to 31 March [95% credible interval 21,000-120,000]. Many more deaths will be averted through ensuring that interventions remain in place until transmission drops to low levels. We estimate that, across all 11 countries between 7 and 43 million individuals have been infected with SARS-CoV-2 up to 28th March, representing between 1.88% and 11.43% of the population. The proportion of the population infected to date – the attack rate - is estimated to be highest in Spain followed by Italy and lowest in Germany and Norway, reflecting the relative stages of the epidemics. Given the lag of 2-3 weeks between when transmission changes occur and when their impact can be observed in trends in mortality, for most of the countries considered here it remains too early to be certain that recent interventions have been effective. If interventions in countries at earlier stages of their epidemic, such as Germany or the UK, are more or less effective than they were in the countries with advanced epidemics, on which our estimates are largely based, or if interventions have improved or worsened over time, then our estimates of the reproduction number and deaths averted would change accordingly. It is therefore critical that the current interventions remain in place and trends in cases and deaths are closely monitored in the coming days and weeks to provide reassurance that transmission of SARS-Cov-2 is slowing.

Introduction Setting and monitoring progress towards targets for HIV control is critical in ensuring responsive programmes. Here, we explore how to apply targets for reduction in HIV incidence to local settings and which indicators give the strongest signal of a change in incidence in the population and are therefore most important to monitor. Methods We use location‐specific HIV transmission models, tailored to the epidemics in the counties and major cities in Kenya, to project a wide range of plausible future epidemic trajectories through varying behaviours, treatment coverage and prevention interventions. We look at the change in incidence across modelled scenarios in each location between 2015 and 2030 to inform local target setting. We also simulate the measurement of a library of potential indicators and assess which are most strongly associated with a change in incidence. Results Considerable variation was observed in the trajectory of the local epidemics under the plausible scenarios defined (only 10 of 48 locations saw a median reduction in incidence of greater than or equal to an 80% target by 2030). Indicators that provide strong signals in certain epidemic types may not perform consistently well in settings with different epidemiological features. Predicting changes in incidence is more challenging in advanced generalized epidemics compared to concentrated epidemics where changes in high‐risk sub‐populations track more closely to the population as a whole. Many indicators demonstrate only limited association with incidence (such as “condom use” or “pre‐exposure prophylaxis coverage”). This is because many other factors (low effectiveness, impact of other interventions, countervailing changes in risk behaviours, etc.) can confound the relationship between interventions and their ultimate long‐term impact, especially for an intervention with low expected coverage. The population prevalence of viral suppression shows the most consistent associations with long‐term changes in incidence even in the largest generalized epidemics. Conclusions Target setting should be appropriate for the local epidemic and what can feasibly be achieved. There is no one universally reliable indicator to predict future HIV incidence across settings. Thus, the signature of epidemic control must contain indications of success across a wide range of interventions and outcomes.

Introduction: Weaknesses in care programmes providing anti‐retroviral therapy (ART) persist and are often instigated by late HIV diagnosis and poor linkage to care. We investigated the potential for a home‐based counselling and testing (HBCT) campaign to be improved through the optimal timing and enhancement of testing rounds to generate greater health outcomes at minimum cost. Methods: Using a mathematical model of HIV care calibrated to longitudinal data from The Academic Model Providing Access To Healthcare (AMPATH) in Kenya, we simulated HBCT campaigns between 2016 and 2036, assessing the impact and total cost of care for each, for a further 20 years. Results: We find that simulating five equally spaced rounds averts 1.53 million disability‐adjusted life‐years (DALYs) at a cost of $1617 million. By altering the timing of HBCT rounds, a four‐round campaign can produce greater impact for lower cost. With “front‐loaded” rounds, the cost per DALY averted is reduced by 12% as fewer rounds are required ($937 vs. $1060). Furthermore, improvements to HBCT coverage and linkage to care avert over two million DALYs at a cost per DALY averted of $621 (41% less than the reference scenario). Conclusions: Countries implementing HBCT can reduce costs by optimally timing rounds and generate greater health outcomes through improving linkage, coverage, and retention. Tailoring HBCT campaigns to individual settings can enhance patient outcomes for minimal cost.

Purpose: The Manicaland cohort was established to provide robust scientific data on HIV prevalence and incidence, patterns of sexual risk behaviour and the demographic impact of HIV in a sub-Saharan African population subject to a generalised HIV epidemic. The aims were later broadened to include provision of data on the coverage and effectiveness of national HIV control programmes including antiretroviral therapy (ART).Participants: General population open cohort located in 12 sites in Manicaland, east Zimbabwe, representing 4 major socioeconomic strata (small towns, agricultural estates, roadside settlements and subsistence farming areas). 9,109 of 11,453 (79.5%) eligible adults (men 17-54 years; women 15–44 years) were recruited in a phased household census between July 1998 and January 2000. Five rounds of follow-up of the prospective household census and the open cohort were conducted at 2-year or 3-year intervals between July 2001 and November 2013. Follow-up rates among surviving residents ranged between 77.0% (over 3 years) and 96.4% (2 years).Findings to date: HIV prevalence was 25.1% at baseline and had a substantial demographic impact with 10-fold higher mortality in HIV-infected adults than in uninfected adults and a reduction in the growth rate in the worst affected areas (towns) from 2.9% to 1.0%pa. HIV infection rates have been highest in young adults with earlier commencement of sexual activity and in those with older sexual partners and larger numbers of lifetime partners. HIV prevalence has since fallen to 15.8% and HIV incidence has also declined from 2.1% (1998-2003) to 0.63% (2009-2013) largely due to reduced sexual risk behaviour. HIV-associated mortality fell substantially after 2009 with increased availability of ART.Future plans: We plan to extend the cohort to measure the effects on the epidemic of current and future HIV prevention and treatment programmes. Proposals for access to these data and for collaboration are welcome.

Background: The role of PrEP in combination HIV prevention remains uncertain. We aimed to identify an optimal portfolio of interventions to reduce HIV incidence for a given budget, and to identify the circumstances in which PrEP could be used in Nairobi, Kenya. Methods: A mathematical model was developed to represent HIV transmission among specific key populations (female sex workers (FSW), male sex workers (MSW), and men who have sex with men (MSM)) and among the wider population of Nairobi. The scale-up of existing interventions (condom promotion, anti-retroviral therapy (ART) and male circumcision) for key populations and the wider population as have occurred in Nairobi is represented. The model includes a detailed representation of a Pre-Exposure Prophylaxis (PrEP) intervention and is calibrated to prevalence and incidence estimates specific to key populations and the wider population. Findings: In the context of a declining epidemic overall but with a large sub-epidemic among MSM and MSW, an optimal prevention portfolio for Nairobi should focus on condom promotion for MSW and MSM in particular, followed by improved ART retention, earlier ART, and male circumcision as the budget allows. PrEP for MSW could enter an optimal portfolio at similar levels of spending to when earlier ART is included, however PrEP for MSM and FSW would be included only at much higher budgets. If PrEP for MSW cost as much $500, average annual spending on the interventions modelled would need to be less than $3·27 million for PrEP for MSW to be excluded from an optimal portfolio. Estimated costs per infection averted when providing PrEP to all FSW regardless of their risk of infection, and to high risk FSW only, are $65,160 (95% credible interval: $43,520 - $90,250) and $10,920 (95% credible interval: $4,700 - $51,560) respectively. Interpretation: PrEP could be a useful contribution to combination prevention, especially for underserved key populations in Nairobi. An ongoing demonstration project will provide important information regarding practical aspects of implementing PrEP for key populations in this setting.

This article uses a mid-century text to reengage a late-1970s concept to answer a new century question. The authors return to Alvin Gouldner's classic (1954) study Patterns of Industrial Bureaucracy to reexamine the "coupling" concept in contemporary institutionalism in a way that engages the following question: How do new institutional forms emerge? Based on Gouldner's detailed observations of work in a gypsum mine, the authors argue that coupling processes are key mechanisms in the emergence of institutional forms. Examining coupling as a dynamic process and activity helps us to understand how the institution of bureaucracy emerged in the gypsum mine and interacted with previous social orders of authority and control. Gouldner's account of coupling at the mine is a story of formal and informal power struggles and active conflict over meaning, bringing the process of local institutional formation into sharp relief.