Imperial College London

Jeff Eaton

Faculty of MedicineSchool of Public Health

Senior Lecturer in HIV Epidemiology
 
 
 
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jeffrey.eaton

 
 
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Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Publication Type
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115 results found

Eaton J, Dwyer-Lindgren L, Gutreuter S, O'Driscoll M, Stevens O, Bajaj S, Ashton R, Hill A, Russell E, Esra R, Dolan N, Anifowoshe Y, Woodbridge M, Fellows I, Glaubius R, Haeuser E, Okonek T, Stover J, Thomas M, Wakefield J, Wolock T, Berry J, Sabala T, Heard N, Delgado S, Jahn A, Kalua T, Chimpandule T, Auld A, Kim E, Payne D, Johnson LF, Fitzjohn R, Wanyeki I, Mahy M, Shiraishi RWet al., 2021, Naomi: a new modelling tool for estimating HIV epidemic indicators at the district level in Sub-Saharan Africa, Journal of the International AIDS Society, ISSN: 1758-2652

Introduction: HIV planning requires granular estimates for the number of people living withHIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIVinfections by district, or equivalent subnational administrative level. We developed aBayesian small-area estimation model, called Naomi, to estimate these quantities stratifiedby subnational administrative units, sex, and five-year age groups.Methods: Small-area regressions for HIV prevalence, ART coverage, and HIV incidencewere jointly calibrated using subnational household survey data on all three indicators,routine antenatal service delivery data on HIV prevalence and ART coverage amongpregnant women, and service delivery data on the number of PLHIV receiving ART.Incidence was modelled by district-level HIV prevalence and ART coverage. Model outputsof counts and rates for each indicator were aggregated to multiple geographic anddemographic stratifications of interest. The model was estimated in an empirical Bayesframework, furnishing probabilistic uncertainty ranges for all output indicators. Exampleresults were presented using data from Malawi during 2016 to 2018.Results: Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% acrossMalawi’s districts and was higher in southern districts and in metropolitan areas. ARTcoverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIVwere among ages 35-39 for both women and men, while the most untreated PLHIV wereamong ages 25-29 for women and 30-34 for men. Relative uncertainty was larger for theuntreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART atfacilities in Lilongwe City, an estimated 71% (95% CI 61–79%) resided in Lilongwe City, 20%(14–27%) in Lilongwe district outside the metropolis, and 9% (6–12%) in neighbouring Dowadistrict. Thirty-eight percent (26–50%) of Lilongwe Rural residents and 39% (27–50%) ofDowa residents received treatment at facilit

Journal article

Glaubius R, Kothegal N, Birhanu S, Jonnalagadda S, Mahiane SG, Johnson LF, Brown T, Stover J, Mangal T, Pantazis N, Eaton Jet al., 2021, Disease progression and mortality with untreated HIV infection: evidence synthesis of HIV seroconverter cohorts, antiretroviral treatment clinical cohorts, and population-based survey data, Journal of the International AIDS Society, ISSN: 1758-2652

Background: Model-based estimates of key HIV indicators depend on past epidemic trends that arederived based on assumptions about HIV disease progression and mortality in the absence ofantiretroviral treatment (ART). Population-based HIV Impact Assessment (PHIA) household surveysconducted between 2015 and 2018 found substantial numbers of respondents living with untreated HIVinfection. CD4 cell counts measured in these individuals provide novel information to estimate HIVdisease progression and mortality rates off ART.Methods: We used Bayesian multi-parameter evidence synthesis to combine data on i) cross-sectionalCD4 cell counts among untreated adults living with HIV from ten PHIA surveys, ii) survival after HIVseroconversion in East African seroconverter cohorts, and iii) post-seroconversion CD4 counts and iv)mortality rates by CD4 count predominantly from European, North American, and Australianseroconverter cohorts. We used Incremental Mixture Importance Sampling to estimate HIV naturalhistory and ART uptake parameters used in the Spectrum software. We validated modeled trends in CD4count at ART initiation against ART initiator cohorts in sub-Saharan Africa.Results: Median untreated HIV survival decreased with increasing age at seroconversion, from 12.5years (95% credible interval [CrI]: 12.1-12.7) at ages 15-24 to 7.2 years (95% CrI: 7.1-7.7) at ages 45-54.Older age was associated with lower initial CD4 counts, faster CD4 count decline and higher HIV-relatedmortality rates. Our estimates suggested a weaker association between ART uptake and HIV-relatedmortality rates than previously assumed in Spectrum. Modeled CD4 counts in untreated people livingwith HIV matched recent household survey data well, though some intercountry variation in frequenciesof CD4 counts above 500 cells/mm3 was not explained. Trends in CD4 counts at ART initiation werecomparable to data from ART initiator cohorts. An alternate model that stratified progression andmortality rates by sex di

Journal article

Mahiane SG, Eaton J, Glaubius R, Case KK, Sabin K, Marsh Ket al., 2021, Updates to Spectrum’s Case Surveillance and Vital Registration tool for HIV estimates and projections, Journal of the International AIDS Society, ISSN: 1758-2652

Introduction: The Case Surveillance and Vital Registration (CSAVR) model within Spectrum estimates HIV incidence trends from surveillance data on numbers of new HIV diagnoses and HIV-related deaths. This article describes developments of the CSAVR tool to more flexibly model diagnosis rates over time, estimate incidence patterns by sex and age group, and by key population group. Methods: We modelled HIV diagnosis rate trends as a mixture of three factors, including temporal and opportunistic infection components. The tool was expanded to estimate incidence rate ratios by sex and age for countries with disaggregated reporting of new HIV diagnoses and AIDS deaths, and to account for information on key populations such as men who have sex with men (MSM), males who inject drugs (MWID), female sex workers (FSW) and females who inject drugs (FWID). We used a Bayesian framework to calibrate the tool in 71 high-income or low HIV burden countries. Results: Across countries, an estimated median 89% (interquartile range [IQR] 78%-96%) of HIV-positive adults knew their status in 2019. Mean CD4 counts at diagnosis were stable over time, with a median of 456 cells/μl (IQR: 391-508) across countries in 2019. In European countries reporting new HIV diagnoses among key populations median estimated proportions of males that are MSM and MWID was 1.3% (IQR: 0.9%- 2.0%) and 0.56% (IQR: 0.51%- 0.64%), respectively. The median estimated proportions of females that are FSW and FWID were 0.36% (IQR: 0.27%-0.45%) and 0.14 (IQR: 0.13%- 0.15%), respectively. HIV incidence per 100 person-year increased among MSM with median estimates reaching 0.43 (IQR: 0.29-1.73) in 2019, but remained stable in MWID, FSW and FWID, at around 0.12 (IQR: 0.04-1.9), 0.09 (IQR: 0.06-0.69) and 0.13% (IQR: 0.08%-0.91%) in 2019, respectively. Knowledge of HIV status among HIV-positive adults gradually increased since the early 1990s to exceed 75% in more than 75% of countries in 2019 among each key population. Con

Journal article

Godin A, Eaton J, Giguere K, Marsh K, Johnson L, Jahn A, Mbofana F, Ehui E, Maheu-Giroux Met al., 2021, Inferring population HIV incidence trends from surveillance data of recent HIV infection among HIV testing clients, AIDS, ISSN: 0269-9370

Background: Measuring recent HIV infections from routine surveillance systems could allow timely and granular monitoring of HIV incidence patterns. We evaluated the relationship of two recent infection indicators with alternative denominators to true incidence patterns.Methods: We used a mathematical model of HIV testing behaviors, calibrated to population-based surveys and HIV testing services program data, to estimate the number of recent infections diagnosed annually from 2010 to 2019 in Côte d’Ivoire, Malawi, and Mozambique. We compared two different denominators to interpret recency data: i) those at risk of HIV acquisition (HIV-negative tests plus recent infections) and ii) all people testing HIV positive. Sex- and age-specific longitudinal trends in both interpretations were then compared to modeled trends in HIV incidence, testing efforts, and HIV positivity among HIV testing services clients.Results: Over 2010–2019, the annual proportion of the eligible population tested increased in all countries, while positivity decreased. The proportion of recent infections among those at risk of HIV acquisition decreased, similar to declines in HIV incidence among adults (≥15 years old). Conversely, the proportion of recent infections among HIV-positive tests increased. The female-to-male ratio of the proportion testing recent among those at risk was closer to 1 than the true incidence sex ratio.Conclusion: The proportion of recent infections among those at risk of HIV acquisition is more indicative of HIV incidence than the proportion among HIV-positive tests. However, interpreting the observed patterns as surrogate measures for incidence patterns may still be confounded by different HIV testing rates between population groups or over time.

Journal article

Risher K, Cori A, Reniers G, Marston M, Calvert C, Crampin A, Dadirai T, Dube A, Gregson S, Herbst K, Lutalo T, Moorhouse L, Mtenga B, Nabukalu D, Newton R, Price AJ, Tlhajoane M, Todd J, Tomlin K, Urassa M, Vandormael A, Fraser C, Slaymaker E, Eaton Jet al., 2021, Age patterns of HIV incidence in eastern and southern Africa: a collaborative analysis of observational general population cohort studies, The Lancet HIV, Vol: 8, Pages: e429-e439, ISSN: 2405-4704

Background: As the HIV epidemic in sub-Saharan Africa matures, evidence about the age distribution of new HIV infections and how this has changed over the epidemic is needed to guide HIV prevention. We assessed trends in age-specific HIV incidence in six population-based cohort studies in eastern and southern Africa, reporting changes in average age at infection, age distribution of new infections, and birth cohort cumulative incidence. Methods: We used a Bayesian model to reconstruct age-specific HIV incidence from repeated observations of individuals’ HIV serostatus and survival collected among population HIV cohorts in rural Malawi, South Africa, Tanzania, Uganda, and Zimbabwe. The HIV incidence rate by age, time and sex was modelled using smooth splines functions. Incidence trends were estimated separately by sex and study. Estimated incidence and prevalence results for 2000-2017, standardised to study population distribution, were used to estimate average age at infection and proportion of new infections by age. Findings: Age-specific incidence declined at all ages, though the timing and pattern of decline varied by study. The average age at infection was higher in men (cohort means: 27·8-34·6 years) than women (cohort means: 24·8-29·6 years). Between 2000 and 2017, the average age at infection increased slightly: cohort means 0·5-2·8 years among men and -0·2-2·5 years among women. Across studies, between 38-63%(cohort means)of women’s infections were among 15-24-year-olds and between 30-63% of men’s infections were in 20-29-year-olds. Lifetime risk of HIV declined for successive birth cohorts. Interpretation: HIV incidence declined in all age groups and shifted slightly, but not dramatically, to older ages. Disproportionate new HIV infections occur among 15-24-year-old 4women and20-29-year-oldmen, supporting focused prevention in these groups. But 40-60% of infections were outside these

Journal article

Wolock T, Flaxman S, Risher K, Dadirai T, Gregson S, Eaton Jet al., 2021, Evaluating distributional regression strategies for modelling self-reported sexual age-mixing, eLife, Vol: 10, Pages: 1-38, ISSN: 2050-084X

The age dynamics of sexual partnership formation determine patterns of sexually transmitted disease transmission and have long been a focus of researchers studying human immunodeficiency virus. Data on self-reported sexual partner age distributions are available from a variety of sources. We sought to explore statistical models that accurately predict the distribution of sexual partner ages over age and sex. We identified which probability distributions and outcome specifications best captured variation in partner age and quantified the benefits of modelling these data using distributional regression. We found that distributional regression with a sinh-arcsinh distribution replicated observed partner age distributions most accurately across three geographically diverse data sets. This framework can be extended with well-known hierarchical modelling tools and can help improve estimates of sexual age-mixing dynamics.

Journal article

Sartorius B, VanderHeide JD, Yang M, Goosmann EA, Hon J, Haeuser E, Cork MA, Perkins S, Jahagirdar D, Schaeffer LE, Serfes AL, LeGrand KE, Abbastabar H, Abebo ZH, Abosetugn AE, Abu-Gharbieh E, Accrombessi MMK, Adebayo OM, Adegbosin AE, Adekanmbi V, Adetokunboh OO, Adeyinka DA, Ahinkorah BO, Ahmadi K, Ahmed MB, Akalu Y, Akinyemi OO, Akinyemi RO, Aklilu A, Akunna CJ, Alahdab F, Al-Aly Z, Alam N, Alamneh AA, Alanzi TM, Alemu BW, Alhassan RK, Ali T, Alipour V, Amini S, Ancuceanu R, Ansari F, Anteneh ZA, Anvari D, Anwer R, Appiah SCY, Arabloo J, Asemahagn MA, Asghari Jafarabadi M, Asmare WN, Atnafu DD, Atout MMW, Atreya A, Ausloos M, Awedew AF, Ayala Quintanilla BP, Ayanore MA, Aynalem YA, Ayza MA, Azari S, Azene ZN, Babar Z-U-D, Baig AA, Balakrishnan S, Banach M, Bärnighausen TW, Basu S, Bayati M, Bedi N, Bekuma TT, Bezabhe WMM, Bhagavathula AS, Bhardwaj P, Bhattacharyya K, Bhutta ZA, Bibi S, Bikbov B, Birhan TA, Bitew ZW, Bockarie MJ, Boloor A, Brady OJ, Bragazzi NL, Briko AN, Briko NI, Burugina Nagaraja S, Butt ZA, Cárdenas R, Carvalho F, Charan J, Chatterjee S, Chattu SK, Chattu VK, Chowdhury MAK, Chu D-T, Cook AJ, Cormier NM, Cowden RG, Culquichicon C, Dagnew B, Dahlawi SMA, Damiani G, Daneshpajouhnejad P, Daoud F, Daryani A, das Neves J, Davis Weaver N, Derbew Molla M, Deribe K, Desta AA, Deuba K, Dharmaratne SD, Dhungana GP, Diaz D, Djalalinia S, Doku PN, Dubljanin E, Duko B, Eagan AW, Earl L, Eaton JW, Effiong A, El Sayed Zaki M, El Tantawi M, Elayedath R, El-Jaafary SI, Elsharkawy A, Eskandarieh S, Eyawo O, Ezzikouri S, Fasanmi AO, Fasil A, Fauk NK, Feigin VL, Ferede TY, Fernandes E, Fischer F, Foigt NA, Folayan MO, Foroutan M, Francis JM, Fukumoto T, Gad MM, Geberemariyam BS, Gebregiorgis BG, Gebremichael B, Gesesew HA, Getacher L, Ghadiri K, Ghashghaee A, Gilani SA, Ginindza TG, Glagn M, Golechha M, Gona PN, Gubari MIM, Gugnani HC, Guido D, Guled RA, Hall BJ, Hamidi S, Handiso DW, Hargono A, Hashi A, Hassanipour S, Hassankhani H, Hayat K, Herteliu C, Hidru HDDet al., 2021, Subnational mapping of HIV incidence and mortality among individuals aged 15–49 years in sub-Saharan Africa, 2000–18: a modelling study, The Lancet HIV, Vol: 8, Pages: e363-e375, ISSN: 2352-3018

BackgroundHigh-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa.MethodsIn this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit.FindingsThe estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated ra

Journal article

Ehrenkranz P, Rosen S, Boulle A, Eaton J, Fox MP, Ford N, Grimsrud A, Rice BD, Sikazwe I, Holmes CBet al., 2021, The revolving door of HIV care: revising the service delivery cascade to achieve the UNAIDS 95-95-95 goals, PLoS Medicine, Vol: 18, Pages: 1-10, ISSN: 1548-7091

Journal article

Giguere K, Eaton J, Marsh K, Johnson L, Johnson CC, Ehui E, Jahn A, Wanyeki I, Mbofana F, Bakiono F, Mahy M, Maheu-Giroux Met al., 2021, Trends in knowledge of HIV status and efficiency of HIV testing services in sub-Saharan Africa, 2000-20: a modelling study using survey and HIV testing programme data, The Lancet HIV, Vol: 8, Pages: 284-293, ISSN: 2405-4704

Background: Monitoring knowledge of HIV status (KOS) among people living with HIV (PLHIV) is essential for an effective national HIV response. This study estimates progress and gaps in reaching the UNAIDS 2020 target of 90% KOS, and the efficiency of HIV testing services (HTS) in sub-Saharan Africa (SSA), where two thirds of all PLHIV live. Methods: We used data from 183 population-based surveys (N=2·7 million participants) and national HTS programs (N=315 country-years) from 40 countries as inputs into a mathematical model to examine trends in KOS among PLHIV, median time from HIV infection to diagnosis, HIV testing positivity, and proportion of new diagnoses among all positive tests, adjusting for retesting.Findings: Across SSA, KOS steadily increased from 6% (95% credible interval [95%CrI]: 5% to 7%) in 2000 to 84% (95%CrI: 82% to 86%) in 2020. Twelve countries and one region, Southern Africa, reached the 90% target. In 2020, KOS was lower among men (79%) than women (87%) across SSA. PLHIV aged 15-24 years were the least likely to know their status (65%), but the largest gap in terms of absolute numbers was among men aged 35-49 years, with over 700,000 left undiagnosed. As KOS increased from 2000 to 2020, the median time to diagnosis decreased from 10 to 3 years, HIV testing positivity declined from 9% to 3%, and the proportion of first-time diagnoses among all positive tests dropped from 89% to 42%.Interpretation: On the path towards the next UNAIDS target of 95% diagnostic coverage by 2030, and in a context of declining positivity and yield of first-time diagnoses, we need to focus on addressing disparities in KOS. Increasing KOS and treatment coverage among older men could be critical to reduce HIV incidence among women in SSA, and by extension, reducing mother-to-child transmission.

Journal article

Eilerts H, Prieto JR, Eaton J, Reniers Get al., 2021, Age patterns of under-five mortality in sub-Saharan Africa during 1990-2018: a comparison of estimates from demographic surveillance with full birth histories and the historic record, Demographic Research, Vol: 44, Pages: 415-442, ISSN: 1435-9871

BACKGROUND: In Sub-Saharan African countries which often lack high-quality vital registration data, estimates of under-five mortality (U5M) rely heavily on full birth histories (FBHs) collected in surveys and model age patterns of mortality calibrated against vital statistics from other populations. Health and Demographic Surveillance Systems (HDSS) are al-ternate sources of population-based data in much of sub-Saharan Africa, which are less formally utilized in estimation. OBJECTIVE: The objective of this study is to compare the age pattern of U5M in African HDSS with FBHs from the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), the Human Mortality Database (HMD), and model age patterns.METHODS: We examined the relative levels of neonatal, post neonatal, infant, and child mortality across data sources. We directly compared estimates for DHS and MICS subnational regions with HDSS, and used OLS regression to identify data attributes that correlated with the disparity between estimates. RESULTSH: DSS and FBH data suggests that African populations have higher levels of child mortality and lower infant mortality than the historic record. This age pattern is most explicit for Western African populations, but also characterizes data for other sub regions. The comparison between HDSS and FBH suggests that FBH child mortality is biased downward. The comparison is less conclusive for neonatal and infant mortality. CONTRIBUTION: This study questions the practice of using model age patterns derived from largely high-income settings for inferring or correcting U5M estimates for African populations. It also highlights the considerable uncertainty around the consistency of HDSS and FBH estimates of U5M.

Journal article

Xia Y, Milwid RM, Godin A, Boily M-C, Johnson LF, Marsh K, Eaton J, Maheu-Giroux Met al., 2021, Accuracy of self-reported HIV testing history and awareness of HIV-positive status among people living with HIV in four Sub-Saharan African countries, AIDS, Vol: 35, Pages: 503-510, ISSN: 0269-9370

Background: In many countries in Sub-Saharan Africa, self-reported HIV testing history and awareness of HIV-positive status from household surveys are used to estimate the percentage of people living with HIV (PLHIV) who know their HIV status. Despite widespread use, there is limited empirical information on the sensitivity of those self-reports, which can be affected by non-disclosure.Methods: Bayesian latent class models were used to estimate the sensitivity of self-reported HIV testing history and awareness of HIV-positive status in four Population-based HIV Impact Assessment surveys in Eswatini, Malawi, Tanzania, and Zambia. Antiretroviral (ARV) metabolites biomarkers were used to identify persons on treatment who did not accurately report their status. For those without ARV biomarkers, the pooled estimate of non-disclosure among untreated persons was 1.48 higher than those on treatment.Results: Among PLHIV, the model-estimated sensitivity of self-reported HIV testing history ranged from 96% to 99% across surveys. The model-estimated sensitivity of self-reported awareness of HIV status varied from 91% to 97%. Non-disclosure was generally higher among men and those aged 15–24 years. Adjustments for imperfect sensitivity did not substantially influence estimates of PLHIV ever tested (difference <4%) but the proportion of PLHIV aware of their HIV-positive status was higher than the unadjusted proportion (difference <8%).Conclusions: Self-reported HIV testing histories in four Eastern and Southern African countries are generally robust although adjustment for non-disclosure increases estimated awareness of status. These findings can contribute to further refinements in methods for monitoring progress along the HIV testing and treatment cascade.

Journal article

Atchison C, Bowman LR, Vrinten C, Redd R, Pristerà P, Eaton J, Ward Het al., 2021, Early perceptions and behavioural responses during the COVID-19 pandemic: a cross-sectional survey of UK adults., BMJ Open, Vol: 11, Pages: 1-12, ISSN: 2044-6055

OBJECTIVE: To examine risk perceptions and behavioural responses of the UK adult population during the early phase of the COVID-19 epidemic in the UK. DESIGN: A cross-sectional survey. SETTING: Conducted with a nationally representative sample of UK adults within 48 hours of the UK Government advising the public to stop non-essential contact with others and all unnecessary travel. PARTICIPANTS: 2108 adults living in the UK aged 18 years and over. Response rate was 84.3% (2108/2500). Data collected between 17 March and 18 March 2020. MAIN OUTCOME MEASURES: Descriptive statistics for all survey questions, including number of respondents and weighted percentages. Robust Poisson regression used to identify sociodemographic variation in: (1) adoption of social distancing measures, (2) ability to work from home, and (3) ability and (4) willingness to self-isolate. RESULTS: Overall, 1992 (94.2%) respondents reported at least one preventive measure: 85.8% washed their hands with soap more frequently; 56.5% avoided crowded areas and 54.5% avoided social events. Adoption of social distancing measures was higher in those aged over 70 years compared with younger adults aged 18-34 years (adjusted relative risk/aRR: 1.2; 95% CI: 1.1 to 1.5). Those with lowest household income were three times less likely to be able to work from home (aRR: 0.33; 95% CI: 0.24 to 0.45) and less likely to be able to self-isolate (aRR: 0.92; 95% CI: 0.88 to 0.96). Ability to self-isolate was also lower in black and minority ethnic groups (aRR: 0.89; 95% CI: 0.79 to 1.0). Willingness to self-isolate was high across all respondents. CONCLUSIONS: Ability to adopt and comply with certain non-pharmaceutical interventions (NPIs) is lower in the most economically disadvantaged in society. Governments must implement appropriate social and economic policies to mitigate this. By incorporating these differences in NPIs among socioeconomic subpopulations into mathematical models of COV

Journal article

Hsieh YL, Jahn A, Menzies NA, Yaesoubi R, Salomon JA, Girma B, Gunde L, Eaton JW, Auld A, Odo M, Kiyiika CN, Kalua T, Chiwandira B, Mpunga JU, Mbendra K, Corbett L, Hosseinipour MC, Cohen T, Kunkel Aet al., 2020, An evaluation of 6-month versus continuous isoniazid preventive therapy for M. tuberculosis in adults living with HIV/AIDS in Malawi., JAIDS: Journal of Acquired Immune Deficiency Syndromes, Vol: 85, Pages: 643-650, ISSN: 1525-4135

BACKGROUND: To assist the Malawi Ministry of Health to evaluate two competing strategies for scale-up of isoniazid preventive therapy (IPT) among HIV-positive adults receiving ART. SETTING: Malawi. METHODS: We used a multi-district, compartmental model of the Malawi TB/HIV epidemic to compare the anticipated health impacts of 6-month versus continuous IPT programs over a 12-year horizon, while respecting a US$10.8 million constraint on drug costs in the first three years. RESULTS: The 6-month IPT program could be implemented nationwide while the continuous IPT alternative could be introduced in 14 (out of 27) districts. By the end of year 12, the continuous IPT strategy was predicted to avert more TB cases than the 6-month alternative, although not statistically significantly (2368 additional cases averted; 95%PI, -1459, 5023). The 6-month strategy required fewer person-years of IPT to avert a case of TB or death than the continuous strategy. For both programs, the mean reductions in TB incidence among PLHIV by year 12 were expected to be <10%, and the cumulative numbers of IPT-related hepatotoxicity to exceed the number of all-cause deaths averted in the first three years. CONCLUSION: With the given budgetary constraint, nationwide implementation of 6-month IPT would be more efficient and yield comparable health benefits than implementing continuous IPT program in fewer districts. The anticipated health effects associated with both IPT strategies suggested a combination of different TB intervention strategies would likely be required to yield greater impact on TB control in settings like Malawi, where ART coverage is relatively high.

Journal article

Unwin H, Mishra S, Bradley V, Gandy A, Mellan T, Coupland H, Ish-Horowicz J, Vollmer M, Whittaker C, Filippi S, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie K, Baguelin M, Boonyasiri A, Brazeau N, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales O, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hinsley W, Jeffrey B, Knock E, Laydon D, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag K, Siveroni I, Thompson H, Walker P, Walters C, Watson O, Whittles L, Ghani A, Ferguson N, Riley S, Donnelly C, Bhatt S, Flaxman Set al., 2020, State-level tracking of COVID-19 in the United States, Nature Communications, Vol: 11, Pages: 1-9, ISSN: 2041-1723

As of 1st June 2020, the US Centers for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available deathdata within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on therate of transmission of SARS-CoV-2. We estimate thatRtwas only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%-4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

Journal article

Sheng B, Eaton JW, Mahy M, Bao Let al., 2020, Comparison of HIV prevalence among antenatal clinic attendees estimated from routine testing and unlinked anonymous testing, Statistics in Biosciences, Vol: 12, Pages: 279-294, ISSN: 1867-1772

In 2015, WHO and UNAIDS released new guidance recommending that countries transition from conducting antenatal clinic (ANC) unlinked anonymous testing (ANC-UAT) for tracking HIV prevalence trends among pregnant women to using ANC routine testing (ANC-RT) data, which are more consistent and economic to collect. This transition could pose challenges for distinguishing whether changes in observed prevalence are due to a change in underlying population prevalence or due to a change in the testing approach. We compared the HIV prevalence measured from ANC-UAT and ANC-RT in 15 countries that had both data sources in overlapping years. We used linear mixed-effects model (LMM) to estimate the RT-to-UAT calibration parameter as well as other unobserved quantities. We summarized the results at different levels of aggregation (e.g., country, urban, rural, and province). Based on our analysis, the HIV prevalence measured by ANC-UAT and ANC-RT data are consistent in most countries. Therefore, if large discrepancy is observed between ANC-UAT and ANC-RT at the same location, we recommend that people should be cautious and investigate the reason. For countries that lack information to estimate the calibration parameter, we propose an informative prior distribution of mean 0 and standard deviation 0.2 for the RT-to-UAT calibration parameter.

Journal article

Johnson L, Kubjane M, Eaton J, 2020, Challenges in estimating HIV prevalence trends and geographical variation in HIV prevalence using antenatal data: insights from mathematical modelling, PLoS One, Vol: 15, Pages: 1-22, ISSN: 1932-6203

HIV prevalence data among pregnant women have been critical to estimating HIV trends and geographical patterns of HIV in many African countries. Although antenatal HIV prevalence data are known to be biased representations of HIV prevalence in the general population, mathematical models have made various adjustments to control for known sources of bias, including the effect of HIV on fertility, the age profile of pregnant women and sexual experience.<h4>Methods and findings</h4>We assessed whether assumptions about antenatal bias affect conclusions about trends and geographical variation in HIV prevalence, using simulated datasets generated by an agent-based model of HIV and fertility in South Africa. Results suggest that even when controlling for age and other previously-considered sources of bias, antenatal bias in South Africa has not been constant over time, and trends in bias differ substantially by age. Differences in the average duration of infection explain much of this variation. We propose an HIV duration-adjusted measure of antenatal bias that is more stable, which yields higher estimates of HIV incidence in recent years and at older ages. Simpler measures of antenatal bias, which are not age-adjusted, yield estimates of HIV prevalence and incidence that are too high in the early stages of the HIV epidemic, and that are less precise. Antenatal bias in South Africa is substantially greater in urban areas than in rural areas.<h4>Conclusions</h4>Age-standardized approaches to defining antenatal bias are likely to improve precision in model-based estimates, and further recency adjustments increase estimates of HIV incidence in recent years and at older ages. Incompletely adjusting for changing antenatal bias may explain why previous model estimates overstated the early HIV burden in South Africa. New assays to estimate the fraction of HIV-positive pregnant women who are recently infected could play an important role in better estimatin

Journal article

Schafer R, Thomas R, Robertson L, Eaton J, Mushati P, Nyamukapa C, Hauck K, Gregson Set al., 2020, Spillover HIV prevention effects of a cash transfer trial in East Zimbabwe: evidence from a cluster-randomised trial and general-population survey, BMC Public Health, Vol: 20, ISSN: 1471-2458

BackgroundBenefits of cash transfers (CTs) for HIV prevention have been demonstrated largely in purposively designed trials, commonly focusing on young women. It is less clear if CT interventions not designed for HIV prevention can have HIV-specific effects, including adverse effects. The cluster-randomised Manicaland Cash Transfer Trial (2010–11) evaluated effects of CTs on children’s (2–17 years) development in eastern Zimbabwe. We evaluated whether this CT intervention with no HIV-specific objectives had unintended HIV prevention spillover effects (externalities).MethodsData on 2909 individuals (15–54 years) living in trial households were taken from a general-population survey, conducted simultaneously in the same communities as the Manicaland Trial. Average treatment effects (ATEs) of CTs on sexual behaviour (any recent sex, condom use, multiple partners) and secondary outcomes (mental distress, school enrolment, and alcohol/cigarette/drug consumption) were estimated using mixed-effects logistic regressions (random effects for study site and intervention cluster), by sex and age group (15–29; 30–54 years). Outcomes were also evaluated with a larger synthetic comparison group created through propensity score matching.ResultsCTs did not affect sexual debut but reduced having any recent sex (past 30 days) among young males (ATE: − 11.7 percentage points [PP] [95% confidence interval: -26.0PP, 2.61PP]) and females (− 5.68PP [− 15.7PP, 4.34PP]), with similar but less uncertain estimates when compared against the synthetic comparison group (males: -9.68PP [− 13.1PP, − 6.30PP]; females: -8.77PP [− 16.3PP, − 1.23PP]). There were no effects among older individuals. Young (but not older) males receiving CTs reported increased multiple partnerships (8.49PP [− 5.40PP, 22.4PP]; synthetic comparison: 10.3PP (1

Journal article

Xia Y, Milwid R, Godin A, Boily M-C, Johnson L, Marsh K, Eaton J, Maheu-Giroux Met al., 2020, Accuracy of self-reported HIV testing history and awareness of HIV-positive status among people living with HIV in four Sub-Saharan African countries

Background: In many countries in Sub-Saharan Africa, self-reported HIV testing history and awareness of HIV-positive status from household surveys are used to estimate the percentage of people living with HIV (PLHIV) who know their HIV status. Despite widespread use, there is limited empirical information on the sensitivity of those self-reports, which can be affected by non-disclosure. Methods: Bayesian latent class models were used to estimate the sensitivity of self-reported HIV testing history and awareness of HIV-positive status in four Population-based HIV Impact Assessment surveys in Eswatini, Malawi, Tanzania, and Zambia. Antiretroviral (ARV) metabolites biomarkers were used to identify persons on treatment who did not accurately report their status. For those without ARV biomarkers, the pooled estimate of non-disclosure among untreated persons was 1.48 higher than those on treatment. Results: Among PLHIV, the sensitivity of self-reported HIV testing history ranged 96% to 99% across surveys. Sensitivity of self-reported awareness of HIV status varied from 91% to 97%. Non-disclosure was generally higher among men and those aged 15-24 years. Adjustments for imperfect sensitivity did not substantially influence estimates of of PLHIV ever tested (difference <4%) but the proportion of PLHIV aware of their HIV-positive status was higher than the unadjusted proportion (difference <8%). Conclusions: Self-reported HIV testing histories in four Eastern and Southern African countries are generally robust although adjustment for non-disclosure increases estimated awareness of status. These findings can contribute to further refinements in methods for monitoring progress along the HIV testing and treatment cascade.

Working paper

Hogan A, Jewell B, Sherrard-Smith E, Watson O, Whittaker C, Hamlet A, Smith J, Winskill P, Verity R, Baguelin M, Lees J, Whittles L, Ainslie K, Bhatt S, Boonyasiri A, Brazeau N, Cattarino L, Cooper L, Coupland H, Cuomo-Dannenburg G, Dighe A, Djaafara A, Donnelly C, Eaton J, van Elsland S, Fitzjohn R, Fu H, Gaythorpe K, Green W, Haw D, Hayes S, Hinsley W, Imai N, Laydon D, Mangal T, Mellan T, Mishra S, Parag K, Thompson H, Unwin H, Vollmer M, Walters C, Wang H, Ferguson N, Okell L, Churcher T, Arinaminpathy N, Ghani A, Walker P, Hallett Tet al., 2020, Potential impact of the COVID-19 pandemic on HIV, TB and malaria in low- and middle-income countries: a modelling study, The Lancet Global Health, Vol: 8, Pages: e1132-e1141, ISSN: 2214-109X

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

Journal article

Flaxman S, Mishra S, Gandy A, Unwin HJT, Mellan TA, Coupland H, Whittaker C, Zhu H, Berah T, Eaton JW, Monod M, Perez Guzman PN, Schmit N, Cilloni L, Ainslie K, Baguelin M, Boonyasiri A, Boyd O, Cattarino L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Dorigatti I, van Elsland S, Fitzjohn R, Gaythorpe K, Geidelberg L, Grassly N, Green W, Hallett T, Hamlet A, Hinsley W, Jeffrey B, Knock E, Laydon D, Nedjati Gilani G, Nouvellet P, Parag K, Siveroni I, Thompson H, Verity R, Volz E, Walters C, Wang H, Watson O, Winskill P, Xi X, Walker P, Ghani AC, Donnelly CA, Riley SM, Vollmer MAC, Ferguson NM, Okell LC, Bhatt Set al., 2020, Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe, Nature, Vol: 584, Pages: 257-261, ISSN: 0028-0836

Following the emergence of a novel coronavirus1 (SARS-CoV-2) and its spread outside of China, Europe has experienced large epidemics. In response, many European countries have implemented unprecedented non-pharmaceutical interventions such as closure of schools and national lockdowns. We study the impact of major interventions across 11 European countries for the period from the start of COVID-19 until the 4th of May 2020 when lockdowns started to be lifted. Our model calculates backwards from observed deaths to estimate transmission that occurred several weeks prior, allowing for the time lag between infection and death. We use partial pooling of information between countries with both individual and shared effects on the reproduction number. Pooling allows more information to be used, helps overcome data idiosyncrasies, and enables more timely estimates. Our model relies on fixed estimates of some epidemiological parameters such as the infection fatality rate, does not include importation or subnational variation and assumes that changes in the reproduction number are an immediate response to interventions rather than gradual changes in behavior. Amidst the ongoing pandemic, we rely on death data that is incomplete, with systematic biases in reporting, and subject to future consolidation. We estimate that, for all the countries we consider, current interventions have been sufficient to drive the reproduction number Rt below 1 (probability Rt< 1.0 is 99.9%) and achieve epidemic control. We estimate that, across all 11 countries, between 12 and 15 million individuals have been infected with SARS-CoV-2 up to 4th May, representing between 3.2% and 4.0% of the population. Our results show that major non-pharmaceutical interventions and lockdown in particular have had a large effect on reducing transmission. Continued intervention should be considered to keep transmission of SARS-CoV-2 under control.

Journal article

Cork MA, Wilson KF, Perkins S, Collison ML, Deshpande A, Eaton JW, Earl L, Haeuser E, Justman JE, Kinyoki DK, Mayala BK, Mosser JF, Murray CJL, Nkengasong JN, Piot P, Sartorius B, Schaeffer LE, Serfes AL, Sligar A, Steuben KM, Tanser FC, VanderHeide JD, Yang M, Wabiri N, Hay SI, Dwyer-Lindgren Let al., 2020, Mapping male circumcision for HIV prevention efforts in sub-Saharan Africa, BMC Medicine, Vol: 18, ISSN: 1741-7015

BackgroundHIV remains the largest cause of disease burden among men and women of reproductive age in sub-Saharan Africa. Voluntary medical male circumcision (VMMC) reduces the risk of female-to-male transmission of HIV by 50–60%. The World Health Organization (WHO) and Joint United Nations Programme on HIV/AIDS (UNAIDS) identified 14 priority countries for VMMC campaigns and set a coverage goal of 80% for men ages 15–49. From 2008 to 2017, over 18 million VMMCs were reported in priority countries. Nonetheless, relatively little is known about local variation in male circumcision (MC) prevalence.MethodsWe analyzed geo-located MC prevalence data from 109 household surveys using a Bayesian geostatistical modeling framework to estimate adult MC prevalence and the number of circumcised and uncircumcised men aged 15–49 in 38 countries in sub-Saharan Africa at a 5 × 5-km resolution and among first administrative level (typically provinces or states) and second administrative level (typically districts or counties) units.ResultsWe found striking within-country and between-country variation in MC prevalence; most (12 of 14) priority countries had more than a twofold difference between their first administrative level units with the highest and lowest estimated prevalence in 2017. Although estimated national MC prevalence increased in all priority countries with the onset of VMMC campaigns, seven priority countries contained both subnational areas where estimated MC prevalence increased and areas where estimated MC prevalence decreased after the initiation of VMMC campaigns. In 2017, only three priority countries (Ethiopia, Kenya, and Tanzania) were likely to have reached the MC coverage target of 80% at the national level, and no priority country was likely to have reached this goal in all subnational areas.ConclusionsDespite MC prevalence increases in all priority countries since the onset of VMMC campaigns in 2008, MC prevalence remain

Journal article

Revill P, Phillips A, Eaton JW, Hallett TBet al., 2020, Modelling and economic evaluation to inform WHO HIV treatment guidelines, Global Health Economics: Shaping Health Policy In Low- And Middle-income Countries, Pages: 275-285, ISBN: 9789813272361

International organizations influence national-level health sector priorities by affecting how much funding is available for health care delivery within countries and how that funding is used. The setting of guidelines for the management of diseases (e.g. for malaria, child health, nutrition) by the World Health Organization (WHO) exerts particular influence. Guidelines typically provide syntheses of evidence on clinical efficacy and effectiveness and make recommendations for health care best practice. However, for the most part, they do not well inform the allocation of limited available health care resources. Consequentially, they risk encouraging national and international decision-makers to divert resources away from areas of greater potential gains in population health. In this case study, we reflect upon efforts to incorporate economic evidence into the development of the WHO HIV Treatment Guidelines. We describe how the WHO has incorporated economic insight into these and other guidelines. However, even in this case, the processes currently followed for guideline development can limit the extent to which recommendations can draw upon economic evidence. Changes in the way WHO Guidelines are developed and interpreted, and how evidence is used to inform decision-making at the country level, is therefore required. We give our thoughts on what these changes could be.

Book chapter

Mellan T, Hoeltgebaum H, Mishra S, Whittaker C, Schnekenberg R, Gandy A, Unwin H, Vollmer M, Coupland H, Hawryluk I, Rodrigues Faria N, Vesga J, Zhu H, Hutchinson M, Ratmann O, Monod M, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Fraser K, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Okell L, Dorigatti I, Walker P, Ghani A, Riley S, Ferguson N, Donnelly C, Flaxman S, Bhatt Set al., 2020, Report 21: Estimating COVID-19 cases and reproduction number in Brazil

Brazil is an epicentre for COVID-19 in Latin America. In this report we describe the Brazilian epidemicusing three epidemiological measures: the number of infections, the number of deaths and the reproduction number. Our modelling framework requires sufficient death data to estimate trends, and wetherefore limit our analysis to 16 states that have experienced a total of more than fifty deaths. Thedistribution of deaths among states is highly heterogeneous, with 5 states—São Paulo, Rio de Janeiro,Ceará, Pernambuco and Amazonas—accounting for 81% of deaths reported to date. In these states, weestimate that the percentage of people that have been infected with SARS-CoV-2 ranges from 3.3% (95%CI: 2.8%-3.7%) in São Paulo to 10.6% (95% CI: 8.8%-12.1%) in Amazonas. The reproduction number (ameasure of transmission intensity) at the start of the epidemic meant that an infected individual wouldinfect three or four others on average. Following non-pharmaceutical interventions such as school closures and decreases in population mobility, we show that the reproduction number has dropped substantially in each state. However, for all 16 states we study, we estimate with high confidence that thereproduction number remains above 1. A reproduction number above 1 means that the epidemic isnot yet controlled and will continue to grow. These trends are in stark contrast to other major COVID19 epidemics in Europe and Asia where enforced lockdowns have successfully driven the reproductionnumber below 1. While the Brazilian epidemic is still relatively nascent on a national scale, our resultssuggest that further action is needed to limit spread and prevent health system overload.

Report

Vollmer M, Mishra S, Unwin H, Gandy A, Melan T, Bradley V, Zhu H, Coupland H, Hawryluk I, Hutchinson M, Ratmann O, Monod M, Walker P, Whittaker C, Cattarino L, Ciavarella C, Cilloni L, Ainslie K, Baguelin M, Bhatia S, Boonyasiri A, Brazeau N, Charles G, Cooper L, Cucunuba Perez Z, Cuomo-Dannenburg G, Dighe A, Djaafara A, Eaton J, van Elsland S, Fitzjohn R, Gaythorpe K, Green W, Hayes S, Imai N, Jeffrey B, Knock E, Laydon D, Lees J, Mangal T, Mousa A, Nedjati Gilani G, Nouvellet P, Olivera Mesa D, Parag K, Pickles M, Thompson H, Verity R, Walters C, Wang H, Wang Y, Watson O, Whittles L, Xi X, Ghani A, Riley S, Okell L, Donnelly C, Ferguson N, Dorigatti I, Flaxman S, Bhatt Set al., 2020, Report 20: A sub-national analysis of the rate of transmission of Covid-19 in Italy

Italy was the first European country to experience sustained local transmission of COVID-19. As of 1st May 2020, the Italian health authorities reported 28; 238 deaths nationally. To control the epidemic, the Italian government implemented a suite of non-pharmaceutical interventions (NPIs), including school and university closures, social distancing and full lockdown involving banning of public gatherings and non essential movement. In this report, we model the effect of NPIs on transmission using data on average mobility. We estimate that the average reproduction number (a measure of transmission intensity) is currently below one for all Italian regions, and significantly so for the majority of the regions. Despite the large number of deaths, the proportion of population that has been infected by SARS-CoV-2 (the attack rate) is far from the herd immunity threshold in all Italian regions, with the highest attack rate observed in Lombardy (13.18% [10.66%-16.70%]). Italy is set to relax the currently implemented NPIs from 4th May 2020. Given the control achieved by NPIs, we consider three scenarios for the next 8 weeks: a scenario in which mobility remains the same as during the lockdown, a scenario in which mobility returns to pre-lockdown levels by 20%, and a scenario in which mobility returns to pre-lockdown levels by 40%. The scenarios explored assume that mobility is scaled evenly across all dimensions, that behaviour stays the same as before NPIs were implemented, that no pharmaceutical interventions are introduced, and it does not include transmission reduction from contact tracing, testing and the isolation of confirmed or suspected cases. We find that, in the absence of additional interventions, even a 20% return to pre-lockdown mobility could lead to a resurgence in the number of deaths far greater than experienced in the current wave in several regions. Future increases in the number of deaths will lag behind the increase in transmission intensity and so a

Report

Atchison C, Bowman L, Eaton J, Imai N, Redd R, Pristera P, Vrinten C, Ward Het al., 2020, Report 10: Public response to UK Government recommendations on COVID-19: population survey, 17-18 March 2020, 10

On Monday 16th March 2020 the UK government announced new actions to control COVID-19. These recommendations directly affected the entire UK population, and included the following: stop non-essential contact with others; stop all unnecessary travel; start working from home where possible; avoid pubs, clubs, theatres and other such social venues; and to isolate at home for 14 days if anyone in the household has a high temperature or a new and continuous cough. To capture public sentiment towards these recommendations, a YouGov survey was commissioned by the Patient Experience Research Centre (PERC), Imperial College London. The survey was completed by 2,108 UK adults between the dates of 17th – 18th March 2020. The survey results show the following:• 77% reported being worried about the COVID-19 outbreak in the UK.• 48% of adults who have not tested positive for COVID-19 believe it is likely they will be infected at some point in the future.• 93% of adults reported personally taking at least one measure to protect themselves from COVID-19 infection, including:o 83% washed their hands more frequently;o 52% avoided crowded areas;o 50% avoided social events;o 36% avoided public transport;o 31% avoided going out;o 11% avoided going to work;o 28% avoided travel to areas outside the UK.• There is high reported ability and willingness to self-isolate for 7 days* if advised to do so by a health professional (88%).• However only 44% reported being able to work from home. This was higher among managerial and professional workers (60%) than manual, semi-skilled, and casual workers (19%)^, reflecting less flexible job roles for manual and lower grade workers. • 71% reported changing behaviour in response to government guidance. The figure (53%) was lower for young adults (18-24 year-olds).• Hand washing (63%), avoiding persons with symptoms (61%), and covering your sneeze (53%) were more likely to be perceived as ‘very effective&rs

Report

Berman P, Revill P, Phillips A, Eaton JW, Hallett TBet al., 2020, Modelling and Economic Evaluation to Inform WHO HIV Treatment Guidelines, World Scientific Series in Global Health Economics and Public Policy, Pages: 275-285

International organizations influence national-level health sector priorities by affecting how much funding is available for health care delivery within countries and how that funding is used. The setting of guidelines for the management of diseases (e.g. for malaria, child health, nutrition) by the World Health Organization (WHO) exerts particular influence. Guidelines typically provide syntheses of evidence on clinical efficacy and effectiveness and make recommendations for health care best practice. However, for the most part, they do not well inform the allocation of limited available health care resources. Consequentially, they risk encouraging national and international decision-makers to divert resources away from areas of greater potential gains in population health. In this case study, we reflect upon efforts to incorporate economic evidence into the development of the WHO HIV Treatment Guidelines. We describe how the WHO has incorporated economic insight into these and other guidelines. However, even in this case, the processes currently followed for guideline development can limit the extent to which recommendations can draw upon economic evidence. Changes in the way WHO Guidelines are developed and interpreted, and how evidence is used to inform decision-making at the country level, is therefore required. We give our thoughts on what these changes could be.

Book chapter

Johnson LF, Anderegg N, Zaniewski E, Eaton JW, Rebeiro PF, Carriquiry G, Nash D, Yotebieng M, Ekouevi DK, Holmes CB, Choi JY, Jiamsakul A, Bakoyannis G, Althoff KN, Sohn AH, Yiannoutsos C, Egger M, International epidemiology Databases to Evaluate AIDS IeDEA Collaborationet al., 2019, Global variations in mortality in adults after initiating antiretroviral treatment: an updated analysis of the International epidemiology Databases to Evaluate AIDS cohort collaboration., AIDS, Vol: 33, Pages: S283-S294, ISSN: 0269-9370

BACKGROUND: UNAIDS models use data from the International epidemiology Databases to Evaluate AIDS (IeDEA) collaboration in setting assumptions about mortality rates after antiretroviral treatment (ART) initiation. This study aims to update these assumptions with new data, to quantify the extent of regional variation in ART mortality and to assess trends in ART mortality. METHODS: Adult ART patients from Africa, Asia and the Americas were included if they had a known date of ART initiation during 2001-2017 and a baseline CD4 cell count. In cohorts that relied only on passive follow-up (no patient tracing or linkage to vital registration systems), mortality outcomes were imputed in patients lost to follow-up based on a meta-analysis of tracing study data. Poisson regression models were fitted to the mortality data. RESULTS: 464 048 ART patients were included. In multivariable analysis, mortality rates were lowest in Asia and highest in Africa, with no significant differences between African regions. Adjusted mortality rates varied significantly between programmes within regions. Mortality rates in the first 12 months after ART initiation were significantly higher during 2001-2006 than during 2010-2014, although the difference was more substantial in Asia and the Americas [adjusted incidence rate ratio (aIRR) 1.43, 95% CI: 1.22-1.66] than in Africa (aIRR 1.07, 95% CI: 1.04-1.11). CONCLUSION: There is substantial variation in ART mortality between and within regions, even after controlling for differences in mortality by age, sex, baseline CD4 category and calendar period. ART mortality rates have declined substantially over time, although declines have been slower in Africa.

Journal article

Eaton JW, Brown T, Puckett R, Glaubius R, Mutai K, Bao L, Salomon JA, Stover J, Mahy M, Hallett TBet al., 2019, The estimation and projection package age-sex model and the r-hybrid model: new tools for estimating HIV incidence trends in sub-Saharan Africa., AIDS, Vol: 33, Pages: S235-S244, ISSN: 0269-9370

OBJECTIVES: Improve models for estimating HIV epidemic trends in sub-Saharan Africa (SSA). DESIGN: Mathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data. METHODS: We modified EPP to incorporate age and sex stratification (EPP-ASM) to more accurately capture the shifting demographics of maturing HIV epidemics. Secondly, we developed a new functional form for the HIV transmission rate, termed 'r-hybrid', which combines a four-parameter logistic function for the initial epidemic growth, peak, and decline followed by a first-order random walk for recent trends after epidemic stabilization. We fitted the r-hybrid model along with previously developed r-spline and r-trend models to HIV prevalence data from household surveys and ANC-SS in 177 regions in 34 SSA countries. We used leave-one-out cross validation with household survey HIV prevalence to compare model predictions. RESULTS: The r-hybrid and r-spline models typically provided similar HIV prevalence trends, but sometimes qualitatively different assessments of recent incidence trends because of different structural assumptions about the HIV transmission rate. The r-hybrid model had the lowest average continuous ranked probability score, indicating the best model predictions. Coverage of 95% posterior predictive intervals was 91.5% for the r-hybrid model, versus 87.2 and 85.5% for r-spline and r-trend, respectively. CONCLUSION: The EPP-ASM and r-hybrid models improve consistency of EPP and Spectrum, improve the epidemiological assumptions underpinning recent HIV incidence estimates, and improve estimates and short-term projections of HIV prevalence trends. Countries that use general population survey and ANC-SS data to estimate HIV epidemic trends should consider using these tools.

Journal article

Maheu-Giroux M, Marsh K, Doyle C, Godin A, Delaunay CL, Johnson LF, Jahn A, Abo K, Mbofana F, Boily M-C, Buckeridge DL, Hankins C, Eaton JWet al., 2019, National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the "first 90" from program and survey data, AIDS, Vol: 33, Pages: S255-S269, ISSN: 0269-9370

OBJECTIVE: HIV testing services (HTS) are a crucial component of national HIV responses. Learning one's HIV diagnosis is the entry point to accessing life-saving antiretroviral treatment and care. Recognizing the critical role of HTS, the Joint United Nations Programme on HIV/AIDS (UNAIDS) launched the 90-90-90 targets stipulating that by 2020, 90% of people living with HIV know their status, 90% of those who know their status receive antiretroviral therapy, and 90% of those on treatment have a suppressed viral load. Countries will need to regularly monitor progress on these three indicators. Estimating the proportion of people living with HIV who know their status (i.e., the "first 90"), however, is difficult. METHODS: We developed a mathematical model (henceforth referred to as "F90") that formally synthesizes population-based survey and HTS program data to estimate HIV status awareness over time. The proposed model uses country-specific HIV epidemic parameters from the standard UNAIDS Spectrum model to produce outputs that are consistent with other national HIV estimates. The F90 model provides estimates of HIV testing history, diagnosis rates, and knowledge of HIV status by age and sex. We validate the F90 model using both in-sample comparisons and out-of-sample predictions using data from three countries: Côte d'Ivoire, Malawi, and Mozambique. RESULTS: In-sample comparisons suggest that the F90 model can accurately reproduce longitudinal sex-specific trends in HIV testing. Out-of-sample predictions of the fraction of PLHIV ever tested over a 4-to-6-year time horizon are also in good agreement with empirical survey estimates. Importantly, out-of-sample predictions of HIV knowledge are consistent (i.e., within 4% points) with those of the fully calibrated model in the three countries when HTS program data are included. The F90 model's predictions of knowledge of status are higher than available self-reported HIV awareness estimates, howe

Journal article

Case K, Johnson L, Mahy M, Marsh K, Supervie V, Eaton Jet al., 2019, Summarizing the results and methods of the 2019 Joint United Nations Programme on HIV/AIDS HIV estimates, AIDS, Vol: 33, Pages: S197-S201, ISSN: 0269-9370

UNAIDS and other partners provide support to countries to develop estimates of HIV and related indicators on an annual basis. These estimates are used to monitor epidemic trends, guide program planning and resource allocation, and inform policy decision-making. The collection of articles in this AIDS supplement provide the headline results for the 2019 UNAIDS estimates and describe the new developments in the methods used to produce these estimates.

Journal article

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