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O'Brien ML, Zimmermann M, Eitmann L, Chao DL, Proctor JL. Contraceptive Adoption and Changes in Empowerment in Kenya, Nigeria, and Senegal. Stud Fam Plann 2023; 54:609-623. [PMID: 37531224 DOI: 10.1111/sifp.12250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
Women's empowerment and contraceptive use are critical to achieving gender equality. The positive association between more empowered women and higher rates of contraceptive use has been well-established by cross-sectional research. However, there remains a gap in understanding the longitudinal relationship between contraceptive adoption and changes to women's empowerment. This study represents a novel approach to understanding the relationship between contraceptive adoption and women's empowerment longitudinally, at the individual level. To the authors' knowledge, this is the first attempt to measure the relationship between contraceptive adoption and women's empowerment using more than one wave of panel data. We leverage the longitudinal design of the Urban Reproductive Health Initiative data to code empowerment items by change over time (e.g., more empowered, no change, less empowered). We use sparse principal component analysis to establish empowerment change domains and calculate individual scores standardized by country-level averages. We estimate mixed effects models on these change domains, to investigate the link between contraceptive adoption and empowerment. We find common themes in empowerment across contexts-but contraceptive adoption has both positive and negative effects on those domains, and this varies across context. We discuss the need for cohort studies to examine this relationship.
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Chao DL, Arzika AM, Abdou A, Maliki R, Karamba A, Galo N, Beidi D, Harouna N, Abarchi M, Root E, Mishra A, Lebas E, Arnold BF, Oldenburg CE, Keenan JD, Lietman TM, O’Brien KS. Distance to Health Centers and Effectiveness of Azithromycin Mass Administration for Children in Niger: A Secondary Analysis of the MORDOR Cluster Randomized Trial. JAMA Netw Open 2023; 6:e2346840. [PMID: 38100110 PMCID: PMC10724761 DOI: 10.1001/jamanetworkopen.2023.46840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 10/13/2023] [Indexed: 12/18/2023] Open
Abstract
Importance The MORDOR (Macrolides Oraux pour Réduire les Décès avec un Oeil sur la Résistance) trial demonstrated that mass azithromycin administration reduced mortality by 18% among children aged 1 to 59 months in Niger. The identification of high-risk subgroups to target with this intervention could reduce the risk of antimicrobial resistance. Objective To evaluate whether distance to the nearest primary health center modifies the effect of azithromycin administration to children aged 1 to 59 months on child mortality. Design, Setting, and Participants The MORDOR cluster randomized trial was conducted from December 1, 2014, to July 31, 2017; this post hoc secondary analysis was conducted in 2023 among 594 clusters (communities or grappes) in the Boboye and Loga departments in Niger. All children aged 1 to 59 months in eligible communities were evaluated. Interventions Biannual (twice-yearly) administration of a single dose of oral azithromycin or matching placebo over 2 years. Main Outcomes and Measures A population-based census was used to monitor mortality and person-time at risk (trial primary outcome). Community distance to a primary health center was calculated as kilometers between the center of each community and the nearest health center. Negative binomial regression was used to evaluate the interaction between distance and the effect of azithromycin on the incidence of all-cause mortality among children aged 1 to 59 months. Results Between December 1, 2014, and July 31, 2017, a total of 594 communities were enrolled, with 76 092 children (mean [SD] age, 31 [2] months; 39 022 [51.3%] male) included at baseline, for a mean (SD) of 128 (91) children per community. Median (IQR) distance to the nearest primary health center was 5.0 (3.2-7.1) km. Over 2 years, 145 693 person-years at risk were monitored and 3615 deaths were recorded. Overall, mortality rates were 27.5 deaths (95% CI, 26.2-28.7 deaths) per 1000 person-years at risk in the placebo arm and 22.5 deaths (95% CI, 21.4-23.5 deaths) per 1000 person-years at risk in the azithromycin arm. For each kilometer increase in distance in the placebo arm, mortality increased by 5% (adjusted incidence rate ratio, 1.05; 95% CI, 1.03-1.07; P < .001). The effect of azithromycin on mortality varied significantly by distance (interaction P = .02). Mortality reduction with azithromycin compared with placebo was 0% at 0 km from the health center (95% CI, -19% to 17%), 4% at 1 km (95% CI, -12% to 17%), 16% at 5 km (95% CI, 7% to 23%), and 28% at 10 km (95% CI, 17% to 38%). Conclusions and Relevance In this secondary analysis of a cluster randomized trial of mass azithromycin administration for child mortality, children younger than 5 years who lived farthest from health facilities appeared to benefit the most from azithromycin administration. These findings may help guide the allocation of resources to ensure that those with the least access to existing health resources are prioritized in program implementation. Trial Registration ClinicalTrials.gov Identifier: NCT02047981.
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Affiliation(s)
| | - Ahmed M. Arzika
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Amza Abdou
- Programme Nationale de Santé Oculaire, Niamey, Niger
| | - Ramatou Maliki
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Alio Karamba
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Nasser Galo
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Diallo Beidi
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Nasser Harouna
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | - Moustapha Abarchi
- Centre de Recherche et Interventions en Santé Publique, Birni N’Gaoure, Niger
| | | | - Anu Mishra
- Bill & Melinda Gates Foundation, Seattle, Washington
| | - Elodie Lebas
- Francis I. Proctor Foundation, University of California, San Francisco
| | - Benjamin F. Arnold
- Francis I. Proctor Foundation, University of California, San Francisco
- Department of Ophthalmology, University of California, San Francisco
| | - Catherine E. Oldenburg
- Francis I. Proctor Foundation, University of California, San Francisco
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Jeremy D. Keenan
- Francis I. Proctor Foundation, University of California, San Francisco
- Department of Ophthalmology, University of California, San Francisco
| | - Thomas M. Lietman
- Francis I. Proctor Foundation, University of California, San Francisco
- Department of Ophthalmology, University of California, San Francisco
- Department of Epidemiology and Biostatistics, University of California, San Francisco
- Institute for Global Health Sciences, University of California, San Francisco
| | - Kieran S. O’Brien
- Francis I. Proctor Foundation, University of California, San Francisco
- Department of Ophthalmology, University of California, San Francisco
- Department of Epidemiology and Biostatistics, University of California, San Francisco
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Brintz BJ, Colston JM, Ahmed SM, Chao DL, Zaitschik B, Leung DT. Assessment of Model Estimated and Directly Observed Weather Data for Etiological Prediction of Diarrhea. medRxiv 2023:2023.10.12.23296959. [PMID: 37873274 PMCID: PMC10593035 DOI: 10.1101/2023.10.12.23296959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Recent advances in clinical prediction for diarrheal etiology in low- and middle-income countries have revealed that addition of weather data improves predictive performance. However, the optimal source of weather data remains unclear. We aim to compare model estimated satellite- and ground-based observational data with weather station directly-observed data for diarrheal prediction. We used clinical and etiological data from a large multi-center study of children with diarrhea to compare these methods. We show that the two sources of weather conditions perform similarly in most locations. We conclude that while model estimated data is a viable, scalable tool for public health interventions and disease prediction, directly observed weather station data approximates the modeled data, and given its ease of access, is likely adequate for prediction of diarrheal etiology in children in low- and middle-income countries.
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Affiliation(s)
- Ben J Brintz
- Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Josh M Colston
- Division of Infectious Diseases and International Health, University of Virginia School of Medicine, USA
| | - Sharia M Ahmed
- Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Dennis L Chao
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Ben Zaitschik
- Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, Maryland Foundation, Seattle, WA, USA
| | - Daniel T Leung
- Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City, UT, USA
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4
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Chao DL, Oron AP, Chabot-Couture G, Sopekan A, Nnebe-Agumadu U, Bates I, Piel FB, Nnodu O. Contribution of malaria and sickle cell disease to anaemia among children aged 6-59 months in Nigeria: a cross-sectional study using data from the 2018 Demographic and Health Survey. BMJ Open 2022; 12:e063369. [PMID: 36385021 PMCID: PMC9670918 DOI: 10.1136/bmjopen-2022-063369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
OBJECTIVES To estimate the fraction of anaemia attributable to malaria and sickle cell disease (SCD) among children aged 6-59 months in Nigeria. DESIGN Cross-sectional analysis of data from Nigeria's 2018 Demographic and Health Survey (DHS). SETTING Nigeria. PARTICIPANTS 11 536 children aged 6-59 months from randomly selected households were eligible for participation, of whom 11 142 had complete and valid biomarker data required for this analysis. Maternal education data were available from 10 305 of these children. PRIMARY OUTCOME MEASURE Haemoglobin concentration. RESULTS We found that 70.6% (95% CI: 62.7% to 78.5%) of severe anaemia was attributable to malaria compared with 12.4% (95% CI: 11.1% to 13.7%) of mild-to-severe and 29.6% (95% CI: 29.6% to 31.8%) of moderate-to-severe anaemia and that SCD contributed 0.6% (95% CI: 0.4% to 0.9%), 1.3% (95% CI: 1.0% to 1.7%) and 10.6% (95% CI: 6.7% to 14.9%) mild-to-severe, moderate-to-severe and severe anaemia, respectively. Sickle trait was protective against anaemia and was associated with higher haemoglobin concentration compared with children with normal haemoglobin (HbAA) among malaria-positive but not malaria-negative children. CONCLUSIONS This approach used offers a new tool to estimate the contribution of malaria to anaemia in many settings using widely available DHS data. The fraction of anaemia among young children in Nigeria attributable to malaria and SCD is higher at more severe levels of anaemia. Prevention of malaria and SCD and timely treatment of affected individuals would reduce cases of severe anaemia.
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Affiliation(s)
- Dennis L Chao
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, Washington, USA
| | - Assaf P Oron
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
| | | | - Alayo Sopekan
- Department of Public Health, Federal Ministry of Health, Abuja, Nigeria
| | - Uche Nnebe-Agumadu
- Department of Paediatrics, University of Abuja College of Health Sciences, Abuja, Nigeria
| | - Imelda Bates
- Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, UK
| | - Frédéric B Piel
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Obiageli Nnodu
- Centre of Excellence for Sickle Cell Disease Research & Training (CESRTA), University of Abuja, Abuja, Nigeria
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Nelson EJ, Khan AI, Keita AM, Brintz BJ, Keita Y, Sanogo D, Islam MT, Khan ZH, Rashid MM, Nasrin D, Watt MH, Ahmed SM, Haaland B, Pavia AT, Levine AC, Chao DL, Kotloff KL, Qadri F, Sow SO, Leung DT. Improving Antibiotic Stewardship for Diarrheal Disease With Probability-Based Electronic Clinical Decision Support: A Randomized Crossover Trial. JAMA Pediatr 2022; 176:973-979. [PMID: 36036920 PMCID: PMC9425282 DOI: 10.1001/jamapediatrics.2022.2535] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
IMPORTANCE Inappropriate use of antibiotics for diarrheal illness can result in adverse effects and increase in antimicrobial resistance. OBJECTIVE To determine whether the diarrheal etiology prediction (DEP) algorithm, which uses patient-specific and location-specific features to estimate the probability that diarrhea etiology is exclusively viral, impacts antibiotic prescriptions in patients with acute diarrhea. DESIGN, SETTING, AND PARTICIPANTS A randomized crossover study was conducted to evaluate the DEP incorporated into a smartphone-based electronic clinical decision-support (eCDS) tool. The DEP calculated the probability of viral etiology of diarrhea, based on dynamic patient-specific and location-specific features. Physicians were randomized in the first 4-week study period to the intervention arm (eCDS with the DEP) or control arm (eCDS without the DEP), followed by a 1-week washout period before a subsequent 4-week crossover period. The study was conducted at 3 sites in Bangladesh from November 17, 2021, to January 21, 2021, and at 4 sites in Mali from January 6, 2021, to March 5, 2021. Eligible physicians were those who treated children with diarrhea. Eligible patients were children between ages 2 and 59 months with acute diarrhea and household access to a cell phone for follow-up. INTERVENTIONS Use of the eCDS with the DEP (intervention arm) vs use of the eCDS without the DEP (control arm). MAIN OUTCOMES AND MEASURES The primary outcome was the proportion of children prescribed an antibiotic. RESULTS A total of 30 physician participants and 941 patient participants (57.1% male; median [IQR] age, 12 [8-18] months) were enrolled. There was no evidence of a difference in the proportion of children prescribed antibiotics by physicians using the DEP (risk difference [RD], -4.2%; 95% CI, -10.7% to 1.0%). In a post hoc analysis that accounted for the predicted probability of a viral-only etiology, there was a statistically significant difference in risk of antibiotic prescription between the DEP and control arms (RD, -0.056; 95% CI, -0.128 to -0.01). No known adverse effects of the DEP were detected at 10-day postdischarge. CONCLUSIONS AND RELEVANCE Use of a tool that provides an estimate of etiological likelihood did not result in a significant change in overall antibiotic prescriptions. Post hoc analysis suggests that a higher predicted probability of viral etiology was linked to reductions in antibiotic use. TRIAL REGISTRATION Clinicaltrials.gov Identifier: NCT04602676.
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Affiliation(s)
- Eric J. Nelson
- Departments of Pediatrics and Environmental and Global Health, Emerging Pathogens Institute, University of Florida, Gainesville
| | - Ashraful I. Khan
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | | | - Ben J. Brintz
- Division of Epidemiology, University of Utah School of Medicine, Salt Lake City
| | | | - Doh Sanogo
- Center for Vaccine Development—Mali, Bamako, Mali
| | - Md Taufiqul Islam
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Zahid Hasan Khan
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Md Mahbubur Rashid
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Dilruba Nasrin
- Center for Vaccine Development and the Department of Pediatrics, University of Maryland, Baltimore
| | - Melissa H. Watt
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Sharia M. Ahmed
- Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City
| | - Ben Haaland
- Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City
| | - Andrew T. Pavia
- Division of Pediatrics Infectious Diseases, University of Utah School of Medicine, Salt Lake City
| | - Adam C. Levine
- Department of Emergency Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Dennis L. Chao
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Karen L. Kotloff
- Center for Vaccine Development and the Department of Pediatrics, University of Maryland, Baltimore
| | - Firdausi Qadri
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Samba O. Sow
- Center for Vaccine Development—Mali, Bamako, Mali
| | - Daniel T. Leung
- Division of Infectious Diseases, University of Utah School of Medicine, Salt Lake City
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Selvaraj P, Wagner BG, Chao DL, Jackson ML, Breugelmans JG, Jackson N, Chang ST. Rural prioritization may increase the impact of COVID-19 vaccines in a representative COVAX AMC country setting due to ongoing internal migration: A modeling study. PLOS Glob Public Health 2022; 2:e0000053. [PMID: 36962090 PMCID: PMC10021691 DOI: 10.1371/journal.pgph.0000053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/15/2021] [Indexed: 11/18/2022]
Abstract
How COVID-19 vaccine is distributed within low- and middle-income countries has received little attention outside of equity or logistical concerns but may ultimately affect campaign impact in terms of infections, severe cases, or deaths averted. In this study we examined whether subnational (urban-rural) prioritization may affect the cumulative two-year impact on disease transmission and burden of a vaccination campaign using an agent-based model of COVID-19 in a representative COVID-19 Vaccines Global Access (COVAX) Advanced Market Commitment (AMC) setting. We simulated a range of vaccination strategies that differed by urban-rural prioritization, age group prioritization, timing of introduction, and final coverage level. Urban prioritization averted more infections in only a narrow set of scenarios, when internal migration rates were low and vaccination was started by day 30 of an outbreak. Rural prioritization was the optimal strategy for all other scenarios, e.g., with higher internal migration rates or later start dates, due to the presence of a large immunological naive rural population. Among other factors, timing of the vaccination campaign was important to determining maximum impact, and delays as short as 30 days prevented larger campaigns from having the same impact as smaller campaigns that began earlier. The optimal age group for prioritization depended on choice of metric, as prioritizing older adults consistently averted more deaths across all of the scenarios. While guidelines exist for these latter factors, urban-rural allocation is an orthogonal factor that we predict to affect impact and warrants consideration as countries plan the scale-up of their vaccination campaigns.
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Affiliation(s)
- Prashanth Selvaraj
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Bradley G. Wagner
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Dennis L. Chao
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, Washington, United States of America
| | | | | | - Nicholas Jackson
- Coalition for Epidemic Preparedness and Innovations, London, United Kingdom
| | - Stewart T. Chang
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, Washington, United States of America
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Chao DL. Mathematical Modeling of Endemic Cholera Transmission. J Infect Dis 2021; 224:S738-S741. [PMID: 34550373 PMCID: PMC8687074 DOI: 10.1093/infdis/jiab472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Mathematical modeling can be used to project the impact of mass vaccination on cholera transmission. Here, we discuss 2 examples for which indirect protection from mass vaccination needs to be considered. In the first, we show that nonvaccinees can be protected by mass vaccination campaigns. This additional benefit of indirect protection improves the cost-effectiveness of mass vaccination. In the second, we model the use of mass vaccination to eliminate cholera. In this case, a high population level of immunity, including contributions from infection and vaccination, is required to reach the “herd immunity” threshold needed to stop transmission and achieve elimination.
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Affiliation(s)
- Dennis L Chao
- Institute for Disease Modeling; Bill & Melinda Gates Foundation, Seattle, Washington, USA
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Nnodu OE, Oron AP, Sopekan A, Akaba GO, Piel FB, Chao DL. Child mortality from sickle cell disease in Nigeria: a model-estimated, population-level analysis of data from the 2018 Demographic and Health Survey. Lancet Haematol 2021; 8:e723-e731. [PMID: 34481551 PMCID: PMC8460996 DOI: 10.1016/s2352-3026(21)00216-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/29/2021] [Accepted: 07/13/2021] [Indexed: 01/19/2023]
Abstract
BACKGROUND Child mortality from sickle cell disease in sub-Saharan Africa is presumed to be high but is not well quantified. This uncertainty contributes to the neglect of sickle cell disease and delays the prioritisation of interventions. In this study, we estimated the mortality of children in Nigeria with sickle cell disease, and the proportion of national under-5 mortality attributable to sickle cell disease. METHODS We did a model-estimated, population-level analysis of data from Nigeria's 2018 Demographic and Health Survey (DHS) to estimate the prevalence and geographical distribution of HbSS and HbSC genotypes assuming Hardy-Weinberg equilibrium near birth. Interviews for the survey were done between Aug 14 and Dec 29, 2018, and the embedded sickle cell disease survey was done in a randomly selected third of the overall survey's households. We developed an approach for estimating child mortality from sickle cell disease by combining information on tested children and their untested siblings. Tested children were aged 6-59 months at the time of the survey. Untested siblings born 0-14 years before the survey were also included in analyses. Testing as part of the DHS was done without regard to disease status. We analysed mortality differences using the inheritance-derived genotypic distribution of untested siblings older than the tested cohort, enabling us to estimate excess mortality from sickle cell disease for the older-sibling cohort (ie, those born between 2003 and 2013). FINDINGS We analysed test results for 11 186 children aged 6-59 months from 7411 households in Nigeria. The estimated average birth prevalence of HbSS was 1·21% (95% CI 1·09-1·37) and was 0·24% (0·19-0·31) for HbSC. We obtained data for estimating child mortality from 10 195 tested children (who could be matched to the individual mother survey) and 17 205 of their untested siblings. 15 227 of the siblings were in the older-sibling cohort. The group of children with sickle cell disease born between 2003 and 2013 with at least one younger sibling in the survey had about 370 excess under-5 deaths per 1000 livebirths (95% CI 150-580; p=0·0008) than children with HbAA. The estimated national average under-5 mortality for children with sickle cell disease born between 2003 and 2013 was 490 per 1000 livebirths (95% CI 270-700), 4·0 times higher (95% CI 2·1-6·0) than children with HbAA. About 4·2% (95% CI 1·7-6·9) of national under-5 mortality was attributable to excess mortality from sickle cell disease. INTERPRETATION The burden of child mortality from sickle cell disease in Nigeria continues to be disproportionately higher than the burden of mortality of children without sickle cell disease. Most of these deaths could be prevented if adequate resources were allocated and available focused interventions were implemented. The methods developed in this study could be used to estimate the burden of sickle cell disease elsewhere in Africa and south Asia. FUNDING Sickle Pan African Research Consortium, and the Bill & Melinda Gates Foundation.
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Affiliation(s)
- Obiageli E Nnodu
- Centre of Excellence for Sickle Cell Disease Research and Training, University of Abuja, Abuja, Nigeria
| | - Assaf P Oron
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Alayo Sopekan
- Sickle Cell Disease Desk, Noncommunicable Diseases Control Programme, Department of Public Health, Federal Ministry of Health, Abuja, Nigeria
| | - Godwin O Akaba
- Department of Obstetrics and Gynaecology, College of Health Sciences, University of Abuja, Abuja, Nigeria
| | - Frédéric B Piel
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Dennis L Chao
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA.
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Levin R, Chao DL, Wenger EA, Proctor JL. Insights into population behavior during the COVID-19 pandemic from cell phone mobility data and manifold learning. Nat Comput Sci 2021; 1:588-597. [PMID: 38217135 PMCID: PMC10766515 DOI: 10.1038/s43588-021-00125-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 08/09/2021] [Indexed: 01/15/2024]
Abstract
Understanding the complex interplay between human behavior, disease transmission and non-pharmaceutical interventions during the COVID-19 pandemic could provide valuable insights with which to focus future public health efforts. Cell phone mobility data offer a modern measurement instrument to investigate human mobility and behavior at an unprecedented scale. We investigate aggregated and anonymized mobility data, which measure how populations at the census-block-group geographic scale stayed at home in California, Georgia, Texas and Washington from the beginning of the pandemic. Using manifold learning techniques, we show that a low-dimensional embedding enables the identification of patterns of mobility behavior that align with stay-at-home orders, correlate with socioeconomic factors, cluster geographically, reveal subpopulations that probably migrated out of urban areas and, importantly, link to COVID-19 case counts. The analysis and approach provide local epidemiologists a framework for interpreting mobility data and behavior to inform policy makers' decision-making aimed at curbing the spread of COVID-19.
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Affiliation(s)
- Roman Levin
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | - Dennis L Chao
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, WA, USA
| | - Edward A Wenger
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, WA, USA
| | - Joshua L Proctor
- Institute for Disease Modeling, Bill and Melinda Gates Foundation, Seattle, WA, USA.
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Brintz BJ, Haaland B, Howard J, Chao DL, Proctor JL, Khan AI, Ahmed SM, Keegan LT, Greene T, Keita AM, Kotloff KL, Platts-Mills JA, Nelson EJ, Levine AC, Pavia AT, Leung DT. A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea. eLife 2021; 10:63009. [PMID: 33527894 PMCID: PMC7853717 DOI: 10.7554/elife.63009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 01/17/2021] [Indexed: 11/13/2022] Open
Abstract
Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where 'pre-test’ epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.
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Affiliation(s)
- Ben J Brintz
- Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, United States.,Division of Infectious Diseases, Department of Internal Medicine, University of Utah, Salt Lake City, United States
| | - Benjamin Haaland
- Population Health Sciences, University of Utah, Salt Lake City, United States
| | - Joel Howard
- Division of Pediatric Infectious Diseases, University of Utah, Salt Lake City, United States
| | - Dennis L Chao
- Institute of Disease Modeling, Bill and Melinda Gates Foundation, Seattle, United States
| | - Joshua L Proctor
- Institute of Disease Modeling, Bill and Melinda Gates Foundation, Seattle, United States
| | - Ashraful I Khan
- International Centre for Diarrhoeal Disease Research, Bangladesh, Dhaka, Bangladesh
| | - Sharia M Ahmed
- Division of Infectious Diseases, Department of Internal Medicine, University of Utah, Salt Lake City, United States
| | - Lindsay T Keegan
- Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, United States
| | - Tom Greene
- Division of Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, United States
| | | | - Karen L Kotloff
- Division of Infectious Disease and Tropical Pediatrics, University of Maryland, Baltimore, United States
| | - James A Platts-Mills
- Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, United States
| | - Eric J Nelson
- Departments of Pediatrics, University of Florida, Gainesville, United States.,Departments of Environmental and Global Health, University of Florida, Gainesville, United States
| | - Adam C Levine
- Department of Emergency Medicine, Brown University, Providence, United States
| | - Andrew T Pavia
- Division of Pediatric Infectious Diseases, University of Utah, Salt Lake City, United States
| | - Daniel T Leung
- Division of Infectious Diseases, Department of Internal Medicine, University of Utah, Salt Lake City, United States.,Division of Microbiology and Immunology, Department of Internal Medicine, University of Utah, Salt Lake City, United States
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11
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Nelson EJ, Grembi JA, Chao DL, Andrews JR, Alexandrova L, Rodriguez PH, Ramachandran VV, Sayeed MA, Wamala JF, Debes AK, Sack DA, Hryckowian AJ, Haque F, Khatun S, Rahman M, Chien A, Spormann AM, Schoolnik GK. Gold Standard Cholera Diagnostics Are Tarnished by Lytic Bacteriophage and Antibiotics. J Clin Microbiol 2020; 58:e00412-20. [PMID: 32611794 PMCID: PMC7448619 DOI: 10.1128/jcm.00412-20] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Accepted: 06/25/2020] [Indexed: 01/22/2023] Open
Abstract
A fundamental, clinical, and scientific concern is how lytic bacteriophage, as well as antibiotics, impact diagnostic positivity. Cholera was chosen as a model disease to investigate this important question, because cholera outbreaks enable large enrollment, field methods are well established, and the predatory relationship between lytic bacteriophage and the etiologic agent Vibrio cholerae share commonalities across bacterial taxa. Patients with diarrheal disease were enrolled at two remote hospitals in Bangladesh. Diagnostic performance was assessed as a function of lytic bacteriophage detection and exposure to the first-line antibiotic azithromycin, detected in stool samples by mass spectrometry. Among diarrheal samples positive by nanoliter quantitative PCR (qPCR) for V. cholerae (n = 78/849), the odds that a rapid diagnostic test (RDT) or qPCR was positive was reduced by 89% (odds ratio [OR], 0.108; 95% confidence interval [CI], 0.002 to 0.872) and 87% (OR, 0.130; 95% CI, 0.022 to 0.649), respectively, when lytic bacteriophage were detected. The odds that an RDT or qPCR was positive was reduced by more than 99% (OR, 0.00; 95% CI, 0.00 to 0.28) and 89% (OR, 0.11; 95% CI, 0.03 to 0.44), respectively, when azithromycin was detected. Analysis of additional samples from South Sudan found similar phage effects on RDTs; antibiotics were not assayed. Cholera burden estimates may improve by accommodating for the negative effects of lytic bacteriophage and antibiotic exposure on diagnostic positivity. One accommodation is using bacteriophage detection as a proxy for pathogen detection. These findings have relevance for other diagnostic settings where bacterial pathogens are vulnerable to lytic bacteriophage predation.
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Affiliation(s)
- E J Nelson
- Departments of Pediatrics and Environmental and Global Health, University of Florida, Gainesville, Florida, USA
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, USA
| | - J A Grembi
- Department of Civil and Environmental Engineering, Stanford University, Stanford, California, USA
| | - D L Chao
- Institute for Disease Modeling, Bellevue, Washington, USA
| | - J R Andrews
- Department of Medicine, School of Medicine, Stanford University, Stanford, California, USA
| | - L Alexandrova
- Vincent Coates Foundation Mass Spectrometry Laboratory, Stanford University, Stanford, California, USA
| | - P H Rodriguez
- Departments of Pediatrics and Environmental and Global Health, University of Florida, Gainesville, Florida, USA
| | - V V Ramachandran
- Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, USA
| | - M A Sayeed
- Departments of Pediatrics and Environmental and Global Health, University of Florida, Gainesville, Florida, USA
| | - J F Wamala
- Country Preparedness and IHR (CPI), World Health Organization (South Sudan), Juba, South Sudan
| | - A K Debes
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - D A Sack
- Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA
| | - A J Hryckowian
- Department of Microbiology, School of Medicine, Stanford University, Stanford, California, USA
| | - F Haque
- Institute of Epidemiology, Disease Control and Research, Ministry of Health and Family Welfare, Government of Bangladesh, Dhaka, Bangladesh
| | - S Khatun
- Institute of Epidemiology, Disease Control and Research, Ministry of Health and Family Welfare, Government of Bangladesh, Dhaka, Bangladesh
| | - M Rahman
- Institute of Epidemiology, Disease Control and Research, Ministry of Health and Family Welfare, Government of Bangladesh, Dhaka, Bangladesh
| | - A Chien
- Vincent Coates Foundation Mass Spectrometry Laboratory, Stanford University, Stanford, California, USA
| | - A M Spormann
- Department of Civil and Environmental Engineering, Stanford University, Stanford, California, USA
| | - G K Schoolnik
- Department of Medicine, School of Medicine, Stanford University, Stanford, California, USA
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12
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Lee EC, Chao DL, Lemaitre JC, Matrajt L, Pasetto D, Perez-Saez J, Finger F, Rinaldo A, Sugimoto JD, Halloran ME, Longini IM, Ternier R, Vissieres K, Azman AS, Lessler J, Ivers LC. Achieving coordinated national immunity and cholera elimination in Haiti through vaccination: a modelling study. Lancet Glob Health 2020; 8:e1081-e1089. [PMID: 32710864 PMCID: PMC7738665 DOI: 10.1016/s2214-109x(20)30310-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 02/17/2020] [Accepted: 05/06/2020] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cholera was introduced into Haiti in 2010. Since then, more than 820 000 cases and nearly 10 000 deaths have been reported. Oral cholera vaccine (OCV) is safe and effective, but has not been seen as a primary tool for cholera elimination due to a limited period of protection and constrained supplies. Regionally, epidemic cholera is contained to the island of Hispaniola, and the lowest numbers of cases since the epidemic began were reported in 2019. Hence, Haiti may represent a unique opportunity to eliminate cholera with OCV. METHODS In this modelling study, we assessed the probability of elimination, time to elimination, and percentage of cases averted with OCV campaign scenarios in Haiti through simulations from four modelling teams. For a 10-year period from January 19, 2019, to Jan 13, 2029, we compared a no vaccination scenario with five OCV campaign scenarios that differed in geographical scope, coverage, and rollout duration. Teams used weekly department-level reports of suspected cholera cases from the Haiti Ministry of Public Health and Population to calibrate the models and used common vaccine-related assumptions, but other model features were determined independently. FINDINGS Among campaigns with the same vaccination coverage (70% fully vaccinated), the median probability of elimination after 5 years was 0-18% for no vaccination, 0-33% for 2-year campaigns focused in the two departments with the highest historical incidence, 0-72% for three-department campaigns, and 35-100% for nationwide campaigns. Two-department campaigns averted a median of 12-58% of infections, three-department campaigns averted 29-80% of infections, and national campaigns averted 58-95% of infections. Extending the national campaign to a 5-year rollout (compared to a 2-year rollout), reduced the probability of elimination to 0-95% and the proportion of cases averted to 37-86%. INTERPRETATION Models suggest that the probability of achieving zero transmission of Vibrio cholerae in Haiti with current methods of control is low, and that bolder action is needed to promote elimination of cholera from the region. Large-scale cholera vaccination campaigns in Haiti would offer the opportunity to synchronise nationwide immunity, providing near-term population protection while improvements to water and sanitation promote long-term cholera elimination. FUNDING Bill & Melinda Gates Foundation, Global Good Fund, Institute for Disease Modeling, Swiss National Science Foundation, and US National Institutes of Health.
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Affiliation(s)
- Elizabeth C Lee
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Joseph C Lemaitre
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Laura Matrajt
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Damiano Pasetto
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland; Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy
| | - Javier Perez-Saez
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Flavio Finger
- Centre for Mathematical Modelling of Infectious Diseases and Department for Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jonathan D Sugimoto
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Ira M Longini
- Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Ralph Ternier
- Partners In Health/Zanmi Lasante, Port-au-Prince, Haiti
| | | | - Andrew S Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Louise C Ivers
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA; Center for Global Health, Massachusetts General Hospital, Boston, MA, USA.
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13
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Oron AP, Chao DL, Ezeanolue EE, Ezenwa LN, Piel FB, Ojogun OT, Uyoga S, Williams TN, Nnodu OE. Caring for Africa's sickle cell children: will we rise to the challenge? BMC Med 2020; 18:92. [PMID: 32340612 PMCID: PMC7187492 DOI: 10.1186/s12916-020-01557-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 03/12/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Most of the world's sickle cell disease (SCD) burden is in Africa, where it is a major contributor to child morbidity and mortality. Despite the low cost of many preventive SCD interventions, insufficient resources have been allocated, and progress in alleviating the SCD burden has lagged behind other public-health efforts in Africa. The recent announcement of massive new funding for research into curative SCD therapies is encouraging in the long term, but over the next few decades, it is unlikely to help Africa's SCD children substantially. MAIN DISCUSSION A major barrier to progress has been the absence of large-scale early-life screening. Most SCD deaths in Africa probably occur before cases are even diagnosed. In the last few years, novel inexpensive SCD point-of-care test kits have become widely available and have been deployed successfully in African field settings. These kits could potentially enable universal early SCD screening. Other recent developments are the expansion of the pneumococcal conjugate vaccine towards near-universal coverage, and the demonstrated safety, efficacy, and increasing availability and affordability of hydroxyurea across the continent. Most elements of standard healthcare for SCD children that are already proven to work in the West, could and should now be implemented at scale in Africa. National and continental SCD research and care networks in Africa have also made substantial progress, assembling care guidelines and enabling the deployment and scale-up of SCD public-health systems. Substantial logistical, cultural, and awareness barriers remain, but with sufficient financial and political will, similar barriers have already been overcome in efforts to control other diseases in Africa. CONCLUSION AND RECOMMENDATIONS Despite remaining challenges, several high-SCD-burden African countries have the political will and infrastructure for the rapid implementation and scale-up of comprehensive SCD childcare programs. A globally funded effort starting with these countries and expanding elsewhere in Africa and to other high-burden countries, including India, could transform the lives of SCD children worldwide and help countries to attain their Sustainable Development Goals. This endeavor would also require ongoing research focused on the unique needs and challenges of SCD patients, and children in particular, in regions of high prevalence.
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Affiliation(s)
- Assaf P Oron
- Maternal, Newborn and Child Health, Institute for Disease Modeling, Bellevue, WA, USA
| | - Dennis L Chao
- Maternal, Newborn and Child Health, Institute for Disease Modeling, Bellevue, WA, USA
| | - Echezona E Ezeanolue
- Healthy Sunrise Foundation, Las Vegas, NV, USA
- College of Medicine, University of Nigeria, Nsukka, Nigeria
| | | | - Frédéric B Piel
- Department of Epidemiology & Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | | | - Sophie Uyoga
- KEMRI-Wellcome Trust Research Programme, PO Box 230, Kilifi, Kenya
| | | | - Obiageli E Nnodu
- Centre of Excellence for Sickle Cell Disease Research & Training, University of Abuja, Abuja, Nigeria
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14
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Chao DL, Roose A, Roh M, Kotloff KL, Proctor JL. The seasonality of diarrheal pathogens: A retrospective study of seven sites over three years. PLoS Negl Trop Dis 2019; 13:e0007211. [PMID: 31415558 PMCID: PMC6711541 DOI: 10.1371/journal.pntd.0007211] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 08/27/2019] [Accepted: 07/26/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource-constrained settings, where nearly all diarrhea-associated mortality occurs, the seasonality of many diarrheal pathogens has not been well characterized. As a retrospective study, we analyze the seasonal prevalence of diarrheal pathogens among children with moderate-to-severe diarrhea (MSD) over three years from the seven sites of the Global Enteric Multicenter Study (GEMS), a case-control study. Using data from this expansive study on diarrheal disease, we characterize the seasonality of different pathogens, their association with site-specific weather patterns, and consistency across study sites. METHODOLOGY/PRINCIPAL FINDINGS Using traditional methodologies from signal processing, we found that certain pathogens peaked at the same time every year, but not at all sites. We also found associations between pathogen prevalence and weather or "seasons," which are defined by applying modern machine-learning methodologies to site-specific weather data. In general, rotavirus was most prevalent during the drier "winter" months and out of phase with bacterial pathogens, which peaked during hotter and rainier times of year corresponding to "monsoon," "rainy," or "summer" seasons. CONCLUSIONS/SIGNIFICANCE Identifying the seasonally-dependent prevalence for diarrheal pathogens helps characterize the local epidemiology and inform the clinical diagnosis of symptomatic children. Our multi-site, multi-continent study indicates a complex epidemiology of pathogens that does not reveal an easy generalization that is consistent across all sites. Instead, our study indicates the necessity of local data to characterizing the epidemiology of diarrheal disease. Recognition of the local associations between weather conditions and pathogen prevalence suggests transmission pathways and could inform control strategies in these settings.
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Affiliation(s)
- Dennis L. Chao
- Institute for Disease Modeling, Bellevue, Washington, United States of America
- * E-mail:
| | - Anna Roose
- Center for Vaccine Development and Global Health, University of Maryland, Baltimore, Maryland, United States of America
| | - Min Roh
- Institute for Disease Modeling, Bellevue, Washington, United States of America
| | - Karen L. Kotloff
- Center for Vaccine Development and Global Health, University of Maryland, Baltimore, Maryland, United States of America
| | - Joshua L. Proctor
- Institute for Disease Modeling, Bellevue, Washington, United States of America
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15
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Fong Y, Halloran ME, Park JK, Marks F, Clemens JD, Chao DL. Efficacy of a bivalent killed whole-cell cholera vaccine over five years: a re-analysis of a cluster-randomized trial. BMC Infect Dis 2018; 18:84. [PMID: 29463233 PMCID: PMC5819652 DOI: 10.1186/s12879-018-2981-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 01/29/2018] [Indexed: 11/10/2022] Open
Abstract
Background Oral cholera vaccine (OCV) is a feasible tool to prevent or mitigate cholera outbreaks. A better understanding of the vaccine’s efficacy among different age groups and how rapidly its protection wanes could help guide vaccination policy. Methods To estimate the level and duration of OCV efficacy, we re-analyzed data from a previously published cluster-randomized, double-blind, placebo controlled trial with five years of follow-up. We used a Cox proportional hazards model and modeled the potentially time-dependent effect of age categories on both vaccine efficacy and risk of infection in the placebo group. In addition, we investigated the impact of an outbreak period on model estimation. Results Vaccine efficacy was 38% (95% CI: -2%,62%) for those vaccinated from ages 1 to under 5 years old, 85% (95% CI: 67%,93%) for those 5 to under 15 years, and 69% (95% CI: 49%,81%) for those vaccinated at ages 15 years and older. Among adult vaccinees, efficacy did not appear to wane during the trial, but there was insufficient data to assess the waning of efficacy among child vaccinees. Conclusions Through this re-analysis we were able to detect a statistically significant difference in OCV efficacy when the vaccine was administered to children under 5 years old vs. children 5 years and older. The estimated efficacies are more similar to the previously published analysis based on the first two years of follow-up than the analysis based on all five years. Trial registration ClinicalTrials.gov identifier NCT00289224 Electronic supplementary material The online version of this article (10.1186/s12879-018-2981-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Youyi Fong
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, 98109, WA, USA.,Department of Biostatistics, School of Public Health, University of Washington, Seattle, 98195, WA, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, 98109, WA, USA.,Department of Biostatistics, School of Public Health, University of Washington, Seattle, 98195, WA, USA
| | - Jin Kyung Park
- Epidemiology Unit, International Vaccine Institute, Seoul, Republic of Korea
| | - Florian Marks
- Epidemiology Unit, International Vaccine Institute, Seoul, Republic of Korea.,The Department of Medicine, The University of Cambridge, Cambridge, United Kingdom
| | | | - Dennis L Chao
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N., Seattle, 98109, WA, USA. .,Institute for Disease Modeling, Intellectual Ventures, Bellevue, 98005, WA, USA.
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16
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Hladish TJ, Pearson CAB, Chao DL, Rojas DP, Recchia GL, Gómez-Dantés H, Halloran ME, Pulliam JRC, Longini IM. Projected Impact of Dengue Vaccination in Yucatán, Mexico. PLoS Negl Trop Dis 2016; 10:e0004661. [PMID: 27227883 PMCID: PMC4882069 DOI: 10.1371/journal.pntd.0004661] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Accepted: 04/02/2016] [Indexed: 01/17/2023] Open
Abstract
Dengue vaccines will soon provide a new tool for reducing dengue disease, but the effectiveness of widespread vaccination campaigns has not yet been determined. We developed an agent-based dengue model representing movement of and transmission dynamics among people and mosquitoes in Yucatán, Mexico, and simulated various vaccine scenarios to evaluate effectiveness under those conditions. This model includes detailed spatial representation of the Yucatán population, including the location and movement of 1.8 million people between 375,000 households and 100,000 workplaces and schools. Where possible, we designed the model to use data sources with international coverage, to simplify re-parameterization for other regions. The simulation and analysis integrate 35 years of mild and severe case data (including dengue serotype when available), results of a seroprevalence survey, satellite imagery, and climatological, census, and economic data. To fit model parameters that are not directly informed by available data, such as disease reporting rates and dengue transmission parameters, we developed a parameter estimation toolkit called AbcSmc, which we have made publicly available. After fitting the simulation model to dengue case data, we forecasted transmission and assessed the relative effectiveness of several vaccination strategies over a 20 year period. Vaccine efficacy is based on phase III trial results for the Sanofi-Pasteur vaccine, Dengvaxia. We consider routine vaccination of 2, 9, or 16 year-olds, with and without a one-time catch-up campaign to age 30. Because the durability of Dengvaxia is not yet established, we consider hypothetical vaccines that confer either durable or waning immunity, and we evaluate the use of booster doses to counter waning. We find that plausible vaccination scenarios with a durable vaccine reduce annual dengue incidence by as much as 80% within five years. However, if vaccine efficacy wanes after administration, we find that there can be years with larger epidemics than would occur without any vaccination, and that vaccine booster doses are necessary to prevent this outcome. Dengue is a mosquito-transmitted viral disease that is common throughout the tropics. Despite a long history in humans and extensive efforts to control dengue transmission in many countries, the number, severity, and geographic range of reported cases is increasing. Most control efforts have focused on controlling mosquito populations, but the main vector, Aedes aegypti, flourishes in human-disturbed and indoor environments. Because the mosquitoes prefer to bite during the day when people are active and potentially moving around high-risk locations, fixed barriers like bed nets are not effective. Several dengue vaccines are being actively developed and may become valuable tools in dengue control. Using historical dengue data from Yucatán, Mexico, we fit a detailed simulation of human and mosquito populations to project future transmission, then used efficacy data from vaccine trials to evaluate the benefit of potential vaccination deployment strategies in the region. For a durable vaccine, we find that population-level, annual vaccine effectiveness approaches 65% by the end of the 20-year forecast period. For waning vaccines, however, effectiveness is greatly reduced–and sometimes negative–unless booster vaccinations are used.
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Affiliation(s)
- Thomas J. Hladish
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- * E-mail:
| | - Carl A. B. Pearson
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Dennis L. Chao
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Diana Patricia Rojas
- Department of Epidemiology, University of Florida, Gainesville, Florida, United States of America
| | - Gabriel L. Recchia
- Institute for Intelligent Systems, University of Memphis, Memphis, Tennessee, United States of America
| | - Héctor Gómez-Dantés
- Health Systems Research Center, National Institute of Public Health, Cuernavaca, Morelos, Mexico
| | - M. Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Center for Inference and Dynamics of Infectious Diseases, Seattle, Washington, United States of America
- Department of Biostatistics, University of Washington, Seattle, Washington, United States of America
| | - Juliet R. C. Pulliam
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Ira M. Longini
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America
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17
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Abstract
Many infectious diseases have seasonal outbreaks, which may be driven by cyclical environmental conditions (e.g., an annual rainy season) or human behavior (e.g., school calendars or seasonal migration). If a pathogen is only transmissible for a limited period of time each year, then seasonal outbreaks could infect fewer individuals than expected given the pathogen's in-season transmissibility. Influenza, with its short serial interval and long season, probably spreads throughout a population until a substantial fraction of susceptible individuals are infected. Dengue, with a long serial interval and shorter season, may be constrained by its short transmission season rather than the depletion of susceptibles. Using mathematical modeling, we show that mass vaccination is most efficient, in terms of infections prevented per vaccine administered, at high levels of coverage for pathogens that have relatively long epidemic seasons, like influenza, and at low levels of coverage for pathogens with short epidemic seasons, like dengue. Therefore, the length of a pathogen's epidemic season may need to be considered when evaluating the costs and benefits of vaccination programs.
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18
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Troeger C, Gaudart J, Truillet R, Sallah K, Chao DL, Piarroux R. Cholera Outbreak in Grande Comore: 1998-1999. Am J Trop Med Hyg 2016; 94:76-81. [PMID: 26572869 PMCID: PMC4710449 DOI: 10.4269/ajtmh.15-0397] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 09/08/2015] [Indexed: 11/07/2022] Open
Abstract
In 1998, a cholera epidemic in east Africa reached the Comoros Islands, an archipelago in the Mozambique Channel that had not reported a cholera case for more than 20 years. In just a little over 1 year (between January 1998 and March 1999), Grande Comore, the largest island in the Union of the Comoros, reported 7,851 cases of cholera, about 3% of the population. Using case reports and field observations during the medical response, we describe the epidemiology of the 1998-1999 cholera epidemic in Grande Comore. Outbreaks of infectious diseases on islands provide a unique opportunity to study transmission dynamics in a nearly closed population, and they may serve as stepping-stones for human pathogens to cross unpopulated expanses of ocean.
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Affiliation(s)
| | | | | | | | - Dennis L. Chao
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington; Sciences Economiques and Sociales de la Santé and Traitement de l'Information Médicale, Aix-Marseille University, Marseille, France; Centre d'Investigation Clinique–Centre de Pharmacologie Clinique et d'Evaluation Thérapeutiques, Assistance Publique Hôpitaux de Marseille, Marseille, France; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington; Aix-Marseille University, Marseilles, France
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19
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Merler S, Ajelli M, Fumanelli L, Gomes MFC, Piontti APY, Rossi L, Chao DL, Longini IM, Halloran ME, Vespignani A. Spatiotemporal spread of the 2014 outbreak of Ebola virus disease in Liberia and the effectiveness of non-pharmaceutical interventions: a computational modelling analysis. Lancet Infect Dis 2015; 15:204-11. [PMID: 25575618 DOI: 10.1016/s1473-3099(14)71074-6] [Citation(s) in RCA: 146] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
BACKGROUND The 2014 epidemic of Ebola virus disease in parts of west Africa defines an unprecedented health threat. We developed a model of Ebola virus transmission that integrates detailed geographical and demographic data from Liberia to overcome the limitations of non-spatial approaches in projecting the disease dynamics and assessing non-pharmaceutical control interventions. METHODS We modelled the movements of individuals, including patients not infected with Ebola virus, seeking assistance in health-care facilities, the movements of individuals taking care of patients infected with Ebola virus not admitted to hospital, and the attendance of funerals. Individuals were grouped into randomly assigned households (size based on Demographic Health Survey data) that were geographically placed to match population density estimates on a grid of 3157 cells covering the country. The spatial agent-based model was calibrated with a Markov chain Monte Carlo approach. The model was used to estimate Ebola virus transmission parameters and investigate the effectiveness of interventions such as availability of Ebola treatment units, safe burials procedures, and household protection kits. FINDINGS Up to Aug 16, 2014, we estimated that 38·3% of infections (95% CI 17·4-76·4) were acquired in hospitals, 30·7% (14·1-46·4) in households, and 8·6% (3·2-11·8) while participating in funerals. We noted that the movement and mixing, in hospitals at the early stage of the epidemic, of patients infected with Ebola virus and those not infected was a sufficient driver of the reported pattern of spatial spread. The subsequent decrease of incidence at country and county level is attributable to the increasing availability of Ebola treatment units (which in turn contributed to drastically decreased hospital transmission), safe burials, and distribution of household protection kits. INTERPRETATION The model allows assessment of intervention options and the understanding of their role in the decrease in incidence reported since Sept 7, 2014. High-quality data (eg, to estimate household secondary attack rate, contact patterns within hospitals, and effects of ongoing interventions) are needed to reduce uncertainty in model estimates. FUNDING US Defense Threat Reduction Agency, US National Institutes of Health.
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Affiliation(s)
| | | | | | - Marcelo F C Gomes
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA
| | - Ana Pastore Y Piontti
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA
| | - Luca Rossi
- Institute for Scientific Interchange, Torino, Italy
| | - Dennis L Chao
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ira M Longini
- Department of Biostatistics, College of Public Health, Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA; Institute for Quantitative Social Sciences at Harvard University, Cambridge, MA, USA.
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Poletto C, Gomes MF, Pastore y Piontti A, Rossi L, Bioglio L, Chao DL, Longini IM, Halloran ME, Colizza V, Vespignani A. Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic. ACTA ACUST UNITED AC 2014; 19. [PMID: 25358040 DOI: 10.2807/1560-7917.es2014.19.42.20936] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The quick spread of an Ebola outbreak in West Africa has led a number of countries and airline companies to issue travel bans to the affected areas. Considering data up to 31 Aug 2014, we assess the impact of the resulting traffic reductions with detailed numerical simulations of the international spread of the epidemic. Traffic reductions are shown to delay by only a few weeks the risk that the outbreak extends to new countries.
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Affiliation(s)
- C Poletto
- INSERM, UMR-S 1136, Institut Pierre Louis d Epidemiologie et de Sante Publique, Paris, France
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Troeger C, Sack DA, Chao DL. Evaluation of targeted mass cholera vaccination strategies in Bangladesh: a demonstration of a new cost-effectiveness calculator. Am J Trop Med Hyg 2014; 91:1181-1189. [PMID: 25294614 PMCID: PMC4257645 DOI: 10.4269/ajtmh.14-0159] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Growing interest in mass vaccination with oral cholera vaccine in endemic and epidemic settings will require policymakers to evaluate how to allocate these vaccines in the most efficient manner. Because cholera, when treated properly, has a low case fatality rate, it may not be economically feasible to vaccinate an entire population. Using a new publicly available calculator for estimating the cost-effectiveness of mass vaccination, we show how targeting high-risk subpopulations for vaccination could be cost-effective in Bangladesh. The approach described here is general enough to adapt to different settings or to other vaccine-preventable diseases.
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Affiliation(s)
| | | | - Dennis L. Chao
- *Address correspondence to Dennis L. Chao, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N, Seattle, WA 98109. E-mail:
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22
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Gog JR, Ballesteros S, Viboud C, Simonsen L, Bjornstad ON, Shaman J, Chao DL, Khan F, Grenfell BT. Spatial Transmission of 2009 Pandemic Influenza in the US. PLoS Comput Biol 2014; 10:e1003635. [PMID: 24921923 PMCID: PMC4055284 DOI: 10.1371/journal.pcbi.1003635] [Citation(s) in RCA: 104] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2013] [Accepted: 04/07/2014] [Indexed: 11/19/2022] Open
Abstract
The 2009 H1N1 influenza pandemic provides a unique opportunity for detailed examination of the spatial dynamics of an emerging pathogen. In the US, the pandemic was characterized by substantial geographical heterogeneity: the 2009 spring wave was limited mainly to northeastern cities while the larger fall wave affected the whole country. Here we use finely resolved spatial and temporal influenza disease data based on electronic medical claims to explore the spread of the fall pandemic wave across 271 US cities and associated suburban areas. We document a clear spatial pattern in the timing of onset of the fall wave, starting in southeastern cities and spreading outwards over a period of three months. We use mechanistic models to tease apart the external factors associated with the timing of the fall wave arrival: differential seeding events linked to demographic factors, school opening dates, absolute humidity, prior immunity from the spring wave, spatial diffusion, and their interactions. Although the onset of the fall wave was correlated with school openings as previously reported, models including spatial spread alone resulted in better fit. The best model had a combination of the two. Absolute humidity or prior exposure during the spring wave did not improve the fit and population size only played a weak role. In conclusion, the protracted spread of pandemic influenza in fall 2009 in the US was dominated by short-distance spatial spread partially catalysed by school openings rather than long-distance transmission events. This is in contrast to the rapid hierarchical transmission patterns previously described for seasonal influenza. The findings underline the critical role that school-age children play in facilitating the geographic spread of pandemic influenza and highlight the need for further information on the movement and mixing patterns of this age group. The determinants of influenza spatial spread are not fully understood, in part due to the insufficient geographic resolution of incidence data. We address this using a fine-grained private sector electronic health database of insurance claims data from health encounters in the US during 2009. We used physician diagnoses codes to generate a dataset of the weekly number of office visits with diagnosed influenza-like illness for 271 US locations. Applying statistical and mathematical models to these disease data, we find that the main autumn wave of the 2009 pandemic in the US was remarkably spatially structured. Its onset in the South Eastern US precipitated a slow radial spread that took 3 months to diffuse across the country. These patterns were replicated by models that included short-distance spatial transmission between nearby locations and increased transmission rates when school was in session. Our results contrast with previous modelling studies that indicated that environmental factors, population sizes, and long-distance transmission events (air traffic) are major determinants in disease spread. We conclude that the 2009 pandemic autumn wave spread slowly because transmissibility of the influenza virus was relatively low and children (who travel long distance far less than adults) were the predominant sources of infection.
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Affiliation(s)
- Julia R. Gog
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail:
| | - Sébastien Ballesteros
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Lone Simonsen
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Global Health, George Washington University, Washington, D.C., United States of America
| | - Ottar N. Bjornstad
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Entomology, Pennsylvania State University, State College, Pennsylvania, United States of America
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Dennis L. Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Farid Khan
- IMS Health, Plymouth Meeting, Pennsylvania, United States of America
| | - Bryan T. Grenfell
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America
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Abstract
Mathematical modeling can be a valuable tool for studying infectious disease outbreak dynamics and simulating the effects of possible interventions. Here, we describe approaches to modeling cholera outbreaks and how models have been applied to explore intervention strategies, particularly in Haiti. Mathematical models can play an important role in formulating and evaluating complex cholera outbreak response options. Major challenges to cholera modeling are insufficient data for calibrating models and the need to tailor models for different outbreak scenarios.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA,
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Abstract
Mathematical modeling can be a valuable tool for studying infectious disease outbreak dynamics and simulating the effects of possible interventions. Here, we describe approaches to modeling cholera outbreaks and how models have been applied to explore intervention strategies, particularly in Haiti. Mathematical models can play an important role in formulating and evaluating complex cholera outbreak response options. Major challenges to cholera modeling are insufficient data for calibrating models and the need to tailor models for different outbreak scenarios.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, USA,
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Chao DL, Longini IM, Halloran ME. The effects of vector movement and distribution in a mathematical model of dengue transmission. PLoS One 2013; 8:e76044. [PMID: 24204590 PMCID: PMC3804532 DOI: 10.1371/journal.pone.0076044] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Accepted: 08/21/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Mathematical models have been used to study the dynamics of infectious disease outbreaks and predict the effectiveness of potential mass vaccination campaigns. However, models depend on simplifying assumptions to be tractable, and the consequences of making such assumptions need to be studied. Two assumptions usually incorporated by mathematical models of vector-borne disease transmission is homogeneous mixing among the hosts and vectors and homogeneous distribution of the vectors. METHODOLOGY/PRINCIPAL FINDINGS We explored the effects of mosquito movement and distribution in an individual-based model of dengue transmission in which humans and mosquitoes are explicitly represented in a spatial environment. We found that the limited flight range of the vector in the model greatly reduced its ability to transmit dengue among humans. A model that does not assume a limited flight range could yield similar attack rates when transmissibility of dengue was reduced by 39%. A model in which mosquitoes are distributed uniformly across locations behaves similarly to one in which the number of mosquitoes per location is drawn from an exponential distribution with a slightly higher mean number of mosquitoes per location. When the models with different assumptions were calibrated to have similar human infection attack rates, mass vaccination had nearly identical effects. CONCLUSIONS/SIGNIFICANCE Small changes in assumptions in a mathematical model of dengue transmission can greatly change its behavior, but estimates of the effectiveness of mass dengue vaccination are robust to some simplifying assumptions typically made in mathematical models of vector-borne disease.
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Affiliation(s)
- Dennis L. Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- * E-mail:
| | - Ira M. Longini
- Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - M. Elizabeth Halloran
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
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Abstract
BACKGROUND The mutations that confer resistance to antiviral agents are thought to be detrimental, or at best neutral, to influenza virus fitness. The fact that resistant influenza strains can circulate and sometimes replace sensitive strains is of great public health concern. OBJECTIVES We used mathematical modeling to test various hypotheses about the transmission of antiviral-resistant influenza viruses by comparing the model's output with the observed rise in antiviral resistance of seasonal A(H1N1) influenza viruses between 2006 and 2009. METHODS We developed a mathematical model of the transmission of influenza among 321 cities around the globe. In the model, influenza strains resistant to antiviral agents competed with sensitive strains. RESULTS AND CONCLUSIONS We found that a resistant strain of influenza could not displace the sensitive strain as rapidly as has been observed unless it was more transmissible than the sensitive strain in the general population. We believe that an antiviral-resistant strain displaced the antiviral-sensitive seasonal A(H1N1) virus by hitchhiking on an escape mutation. Because of the complex global patterns of influenza circulation, tracking the emergence and spread of antiviral resistance must be a coordinated global effort.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
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27
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Willem L, Van Kerckhove K, Chao DL, Hens N, Beutels P. A nice day for an infection? Weather conditions and social contact patterns relevant to influenza transmission. PLoS One 2012; 7:e48695. [PMID: 23155399 PMCID: PMC3498265 DOI: 10.1371/journal.pone.0048695] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2012] [Accepted: 09/28/2012] [Indexed: 11/30/2022] Open
Abstract
Although there is no doubt that significant morbidity and mortality occur during annual influenza epidemics, the role of contextual circumstances, which catalyze seasonal influenza transmission, remains unclear. Weather conditions are believed to affect virus survival, efficiency of transmission and host immunity, but seasonality may also be driven by a tendency of people to congregate indoors during periods of bad weather. To test this hypothesis, we combined data from a social contact survey in Belgium with local weather data. In the absence of a previous in-depth weather impact analysis of social contact patterns, we explored the possibilities and identified pitfalls. We found general dominance of day-type (weekend, holiday, working day) over weather conditions, but nonetheless observed an increase in long duration contacts ([Formula: see text]1 hour) on regular workdays with low temperatures, almost no precipitation and low absolute humidity of the air. Interestingly, these conditions are often assumed to be beneficial for virus survival and transmission. Further research is needed to establish the impact of the weather on social contacts. We recommend that future studies sample over a broad spectrum of weather conditions and day types and include a sufficiently large proportion of holiday periods and weekends.
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Affiliation(s)
- Lander Willem
- Center for Health Economics Research & Modeling of Infectious Diseases, Center for the Evaluation of Vaccinations, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
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Abstract
Background Dengue is a mosquito-borne infectious disease that constitutes a growing global threat with the habitat expansion of its vectors Aedes aegyti and A. albopictus and increasing urbanization. With no effective treatment and limited success of vector control, dengue vaccines constitute the best control measure for the foreseeable future. With four interacting dengue serotypes, the development of an effective vaccine has been a challenge. Several dengue vaccine candidates are currently being tested in clinical trials. Before the widespread introduction of a new dengue vaccine, one needs to consider how best to use limited supplies of vaccine given the complex dengue transmission dynamics and the immunological interaction among the four dengue serotypes. Methodology/Principal Findings We developed an individual-level (including both humans and mosquitoes), stochastic simulation model for dengue transmission and control in a semi-rural area in Thailand. We calibrated the model to dengue serotype-specific infection, illness and hospitalization data from Thailand. Our simulations show that a realistic roll-out plan, starting with young children then covering progressively older individuals in following seasons, could reduce local transmission of dengue to low levels. Simulations indicate that this strategy could avert about 7,700 uncomplicated dengue fever cases and 220 dengue hospitalizations per 100,000 people at risk over a ten-year period. Conclusions/Significance Vaccination will have an important role in controlling dengue. According to our modeling results, children should be prioritized to receive vaccine, but adults will also need to be vaccinated if one wants to reduce community-wide dengue transmission to low levels. An estimated 40% of the world's population is at risk of infection with dengue, a mosquito-borne disease that can lead to hospitalization or death. Dengue vaccines are currently being tested in clinical trials and at least one product will likely be available within a couple of years. Before widespread deployment, one should plan how best to use limited supplies of vaccine. We developed a mathematical model of dengue transmission in semi-rural Thailand to help evaluate different vaccination strategies. Our modeling results indicate that children should be prioritized to receive vaccine to reduce dengue-related morbidity, but adults will also need to be vaccinated if one wants to eliminate local dengue transmission. Dengue is a challenging disease to study because of its four interacting serotypes, seasonality of its transmission, and pre-existing immunity in a population. Models such as this one are useful coherent framework for synthesizing these complex issues and evaluating potential public health interventions such as mass vaccination.
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Affiliation(s)
- Dennis L. Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | | | - M. Elizabeth Halloran
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, Washington, United States of America
| | - Ira M. Longini
- Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- * E-mail:
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Abstract
Resistance to oseltamivir, the most widely used influenza antiviral drug, spread to fixation in seasonal influenza A(H1N1) between 2006 and 2009. This sudden rise in resistance seemed puzzling given the low overall level of the oseltamivir usage and the lack of a correlation between local rates of resistance and oseltamivir usage. We used a stochastic simulation model and deterministic approximations to examine how such events can occur, and in particular to determine how the rate of fixation of the resistant strain depends both on its fitness in untreated hosts as well as the frequency of antiviral treatment. We found that, for the levels of antiviral usage in the population, the resistant strain will eventually spread to fixation, if it is not attenuated in transmissibility relative to the drug-sensitive strain, but not at the speed observed in seasonal H1N1. The extreme speed with which the resistance spread in seasonal H1N1 suggests that the resistant strain had a transmission advantage in untreated hosts, and this could have arisen from genetic hitchhiking, or from the mutations responsible for resistance and compensation. Importantly, our model also shows that resistant virus will fail to spread if it is even slightly less transmissible than its sensitive counterpart--a finding of relevance given that resistant pandemic influenza (H1N1) 2009 may currently suffer from a small, but nonetheless experimentally perceptible reduction in transmissibility.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
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Abstract
Genomic instability, the propensity of aberrations in chromosomes, plays a critical role in the development of many diseases. High throughput genotyping experiments have been performed to study genomic instability in diseases. The output of such experiments can be summarized as high-dimensional binary vectors, where each binary variable records aberration status at one marker locus. It is of keen interest to understand how aberrations may interact with each other, as it provides insight into the process of the disease development. In this article, we propose a novel method, LogitNet, to infer such interactions among these aberration events. The method is based on penalized logistic regression with an extension to account for spatial correlation in the genomic instability data. We conduct extensive simulation studies and show that the proposed method performs well in the situations considered. Finally, we illustrate the method using genomic instability data from breast cancer samples.
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Affiliation(s)
- Pei Wang
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
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Chao DL, Matrajt L, Basta NE, Sugimoto JD, Dean B, Bagwell DA, Oiulfstad B, Halloran ME, Longini IM. Planning for the control of pandemic influenza A (H1N1) in Los Angeles County and the United States. Am J Epidemiol 2011; 173:1121-30. [PMID: 21427173 PMCID: PMC3121321 DOI: 10.1093/aje/kwq497] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2010] [Accepted: 12/15/2010] [Indexed: 11/14/2022] Open
Abstract
Mathematical and computer models can provide guidance to public health officials by projecting the course of an epidemic and evaluating control measures. The authors built upon an existing collaboration between an academic research group and the Los Angeles County, California, Department of Public Health to plan for and respond to the first and subsequent years of pandemic influenza A (H1N1) circulation. The use of models allowed the authors to 1) project the timing and magnitude of the epidemic in Los Angeles County and the continental United States; 2) predict the effect of the influenza mass vaccination campaign that began in October 2009 on the spread of pandemic H1N1 in Los Angeles County and the continental United States; and 3) predict that a third wave of pandemic influenza in the winter or spring of 2010 was unlikely to occur. The close collaboration between modelers and public health officials during pandemic H1N1 spread in the fall of 2009 helped Los Angeles County officials develop a measured and appropriate response to the unfolding pandemic and establish reasonable goals for mitigation of pandemic H1N1.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Ira M. Longini
- Correspondence to Dr. Ira M. Longini Jr., Center for Statistical and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, M2-B865, Seattle, WA (e-mail: )
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Abstract
The opening of schools in the late summer of 2009 may have triggered the fall wave of pandemic influenza A(H1N1) in the United States. We found that an elevated percentage of outpatient visits for influenza-like illness occurred an average of 14 days after schools opened in the fall of 2009. The timing of these events was highly correlated (Spearman correlation coefficient, 0.62; P<.001). This result provides evidence that transmission in schools catalyzes community-wide transmission. School opening dates can be useful for future pandemic planning, and influenza mitigation strategies should be targeted at school populations before the influenza season.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases, Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109-1024, USA.
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Chao DL, Halloran ME, Obenchain VJ, Longini IM. FluTE, a publicly available stochastic influenza epidemic simulation model. PLoS Comput Biol 2010; 6:e1000656. [PMID: 20126529 PMCID: PMC2813259 DOI: 10.1371/journal.pcbi.1000656] [Citation(s) in RCA: 236] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2009] [Accepted: 12/22/2009] [Indexed: 11/22/2022] Open
Abstract
Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development. Computer simulations can provide valuable information to communities preparing for epidemics. These simulations can be used to investigate the effectiveness of various intervention strategies in reducing or delaying the peak of an epidemic. We have made a detailed influenza epidemic simulator for the United States publicly available so that others may use the software to inform public policy or adapt it to suit their needs.
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Affiliation(s)
- Dennis L Chao
- Center for Statistics and Quantitative Infectious Diseases/Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
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Yang Y, Sugimoto JD, Halloran ME, Basta NE, Chao DL, Matrajt L, Potter G, Kenah E, Longini IM. The transmissibility and control of pandemic influenza A (H1N1) virus. Science 2009; 326:729-33. [PMID: 19745114 PMCID: PMC2880578 DOI: 10.1126/science.1177373] [Citation(s) in RCA: 416] [Impact Index Per Article: 27.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Pandemic influenza A (H1N1) 2009 (pandemic H1N1) is spreading throughout the planet. It has become the dominant strain in the Southern Hemisphere, where the influenza season has now ended. Here, on the basis of reported case clusters in the United States, we estimated the household secondary attack rate for pandemic H1N1 to be 27.3% [95% confidence interval (CI) from 12.2% to 50.5%]. From a school outbreak, we estimated that a typical schoolchild infects 2.4 (95% CI from 1.8 to 3.2) other children within the school. We estimated the basic reproductive number, R0, to range from 1.3 to 1.7 and the generation interval to range from 2.6 to 3.2 days. We used a simulation model to evaluate the effectiveness of vaccination strategies in the United States for fall 2009. If a vaccine were available soon enough, vaccination of children, followed by adults, reaching 70% overall coverage, in addition to high-risk and essential workforce groups, could mitigate a severe epidemic.
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Affiliation(s)
- Yang Yang
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
| | - Jonathan D. Sugimoto
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - M. Elizabeth Halloran
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Nicole E. Basta
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Dennis L. Chao
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
| | - Laura Matrajt
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
| | - Gail Potter
- Department of Statistics, University of Washington, Seattle, WA, USA
| | - Eben Kenah
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Ira M. Longini
- Center for Statistics and Quantitative Infectious Diseases, Fred Hutchinson Cancer Research Center and the University of Washington, Seattle, WA, USA
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
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Basta NE, Chao DL, Halloran ME, Matrajt L, Longini IM. Strategies for pandemic and seasonal influenza vaccination of schoolchildren in the United States. Am J Epidemiol 2009; 170:679-86. [PMID: 19679750 PMCID: PMC2737588 DOI: 10.1093/aje/kwp237] [Citation(s) in RCA: 102] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Vaccinating school-aged children against influenza can reduce age-specific and population-level illness attack rates. Using a stochastic simulation model of influenza transmission, the authors assessed strategies for vaccinating children in the United States, varying the vaccine type, coverage level, and reproductive number R (average number of secondary cases produced by a typical primary case). Results indicated that vaccinating children can substantially reduce population-level illness attack rates over a wide range of scenarios. The greatest absolute reduction in influenza illness cases per season occurred at R values ranging from 1.2 to 1.6 for a given vaccine coverage level. The indirect, total, and overall effects of vaccinating children were strong when transmission intensity was low to intermediate. The indirect effects declined rapidly as transmission intensity increased. In a mild influenza season (R = 1.1), approximately 19 million influenza cases could be prevented by vaccinating 70% of children. At most, nearly 100 million cases of influenza illness could be prevented, depending on the proportion of children vaccinated and the transmission intensity. Given the current worldwide threat of novel influenza A (H1N1), with an estimated R of 1.4-1.6, health officials should consider strategies for vaccinating children against novel influenza A (H1N1) as well as seasonal influenza.
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Affiliation(s)
- Nicole E Basta
- Department of Epidemiology,School of Public Health, University of Washington, Seattle,Washington, USA
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Paulson TG, Maley CC, Li X, Li H, Sanchez CA, Chao DL, Odze RD, Vaughan TL, Blount PL, Reid BJ. Chromosomal instability and copy number alterations in Barrett's esophagus and esophageal adenocarcinoma. Clin Cancer Res 2009; 15:3305-14. [PMID: 19417022 DOI: 10.1158/1078-0432.ccr-08-2494] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE Chromosomal instability, as assessed by many techniques, including DNA content aneuploidy, loss of heterozygosity, and comparative genomic hybridization, has consistently been reported to be common in cancer and rare in normal tissues. Recently, a panel of chromosome instability biomarkers, including loss of heterozygosity and DNA content, has been reported to identify patients at high and low risk of progression from Barrett's esophagus (BE) to esophageal adenocarcinoma (EA), but required multiple platforms for implementation. Although chromosomal instability involving amplifications and deletions of chromosome regions have been observed in nearly all cancers, copy number alterations (CNA) in premalignant tissues have not been well characterized or evaluated in cohort studies as biomarkers of cancer risk. EXPERIMENTAL DESIGN We examined CNAs in 98 patients having either BE or EA using Bacterial Artificial Chromosome (BAC) array comparative genomic hybridization to characterize CNAs at different stages of progression ranging from early BE to advanced EA. RESULTS CNAs were rare in early stages (less than high-grade dysplasia) but were progressively more frequent and larger in later stages (high-grade dysplasia and EA), including high-level amplifications. The number of CNAs correlated highly with DNA content aneuploidy. Patients whose biopsies contained CNAs involving >70 Mbp were at increased risk of progression to DNA content abnormalities or EA (hazards ratio, 4.9; 95% confidence interval, 1.6-14.8; P = 0.0047), and the risk increased as more of the genome was affected. CONCLUSIONS Genome-wide analysis of CNAs provides a common platform for the evaluation of chromosome instability for cancer risk assessment as well as for the identification of common regions of alteration that can be further studied for biomarker discovery.
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Affiliation(s)
- Thomas G Paulson
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
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Chao DL, Sanchez CA, Galipeau PC, Blount PL, Paulson TG, Cowan DS, Ayub K, Odze RD, Rabinovitch PS, Reid BJ. Cell proliferation, cell cycle abnormalities, and cancer outcome in patients with Barrett's esophagus: a long-term prospective study. Clin Cancer Res 2008; 14:6988-95. [PMID: 18980994 DOI: 10.1158/1078-0432.ccr-07-5063] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE Elevated cellular proliferation and cell cycle abnormalities, which have been associated with premalignant lesions, may be caused by inactivation of tumor suppressor genes. We measured proliferative and cell cycle fractions of biopsies from a cohort of patients with Barrett's esophagus to better understand the role of proliferation in early neoplastic progression and the association between cell cycle dysregulation and tumor suppressor gene inactivation. EXPERIMENTAL DESIGN Cell proliferative fractions (determined by Ki67/DNA multiparameter flow cytometry) and cell cycle fractions (DNA content flow cytometry) were measured in 853 diploid biopsies from 362 patients with Barrett's esophagus. The inactivation status of CDKN2A and TP53 was assessed in a subset of these biopsies in a cross-sectional study. A prospective study followed 276 of the patients without detectable aneuploidy for an average of 6.3 years with esophageal adenocarcinoma as an end point. RESULTS Diploid S and 4N (G(2)/tetraploid) fractions were significantly higher in biopsies with TP53 mutation and loss of heterozygosity. CDKN2A inactivation was not associated with higher Ki67-positive, diploid S, G(1), or 4N fractions. High Ki67-positive and G(1)-phase fractions were not associated with the future development of esophageal adenocarcinoma (P=0.13 and P=0.15, respectively), whereas high diploid S-phase and 4N fractions were (P=0.03 and P<0.0001, respectively). CONCLUSIONS High Ki67-positive proliferative fractions were not associated with inactivation of CDKN2A and TP53 or future development of cancer in our cohort of patients with Barrett's esophagus. Biallelic inactivation of TP53 was associated with elevated 4N fractions, which have been associated with the future development of esophageal adenocarcinoma.
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Affiliation(s)
- Dennis L Chao
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA.
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Chao DL, Maley CC, Wu X, Farrow DC, Galipeau PC, Sanchez CA, Paulson TG, Rabinovitch PS, Reid BJ, Spitz MR, Vaughan TL. Mutagen Sensitivity and Neoplastic Progression in Patients with Barrett's Esophagus: A Prospective Analysis. Cancer Epidemiol Biomarkers Prev 2006; 15:1935-40. [PMID: 17035402 DOI: 10.1158/1055-9965.epi-06-0492] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Defects in DNA damage recognition and repair have been associated with a wide variety of cancers. We conducted a prospective study to determine whether mutagen sensitivity, as determined by an in vitro assay, was associated with the future development of cancer in patients with Barrett's esophagus, which is associated with increased risk of progression to esophageal adenocarcinoma. METHODS We measured sensitivity to bleomycin in peripheral blood lymphocytes in a cohort of 220 patients with Barrett's esophagus. We followed these patients for 1,230 person-years (range, 3 months to 10.1 years; median, 6.4 years), using development of cancer and aneuploidy as end points. A subset of these patients was evaluated for inactivation of tumor-suppressor genes CDKN2A/p16 and TP53 [by mutation and loss of heterozygosity (LOH)] in their Barrett's segments at the time of, or before, the bleomycin test, and the patients were stratified by CDKN2A/p16 and TP53 status in an analysis of mutagen sensitivity and progression. RESULTS Bleomycin-sensitive patients were found to be at significantly greater risk of developing aneuploidy (adjusted hazard ratio, 3.71; 95% confidence interval, 1.44-9.53) and nonsignificantly greater risk of cancer (adjusted hazard ratio, 1.63; 95% confidence interval, 0.71-3.75). Among patients with detectable LOH at the TP53 locus (on chromosome 17p), increasing bleomycin sensitivity was associated with increased risk of developing cancer (P(trend) < 0.001) and aneuploidy (P(trend) = 0.005). CONCLUSIONS This study supports the hypothesis that sensitivity to mutagens increases the risk of neoplastic progression in persons with Barrett's esophagus, particularly those with 17p LOH including TP53.
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MESH Headings
- Adenocarcinoma/etiology
- Adenocarcinoma/genetics
- Adenocarcinoma/pathology
- Adult
- Aged
- Aneuploidy
- Antibiotics, Antineoplastic/pharmacology
- Barrett Esophagus/complications
- Barrett Esophagus/genetics
- Barrett Esophagus/pathology
- Biomarkers, Tumor/analysis
- Biomarkers, Tumor/genetics
- Bleomycin/pharmacology
- Chromosome Breakage/drug effects
- Chromosomes, Human, Pair 17/drug effects
- Chromosomes, Human, Pair 17/genetics
- Chromosomes, Human, Pair 9/drug effects
- Chromosomes, Human, Pair 9/genetics
- Disease Progression
- Esophageal Neoplasms/etiology
- Esophageal Neoplasms/genetics
- Esophageal Neoplasms/pathology
- Female
- Follow-Up Studies
- Gene Expression Regulation/genetics
- Genes, p16
- Genes, p53/genetics
- Genetic Predisposition to Disease
- Humans
- Loss of Heterozygosity
- Male
- Middle Aged
- Mutagens/analysis
- Precancerous Conditions/genetics
- Precancerous Conditions/pathology
- Prospective Studies
- Sensitivity and Specificity
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Affiliation(s)
- Dennis L Chao
- Division of Human Biology, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, C1-157, Seattle, WA 98109, USA.
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Abstract
Based on the results of a computational model of thymic selection, we propose a mechanism that produces the observed wide range of T cell cross-reactivity. The model suggests that the cross-reactivity of a T cell that survives thymic selection is correlated with its affinity for self peptides. In order to survive thymic selection, a T cell with low affinity for all self peptides expressed in the thymus must have high affinity for major histocompatibility complex (MHC), which makes it highly cross-reactive. A T cell with high affinity for any self peptide must have low MHC affinity to survive selection, which makes it highly specific for its cognate peptide. Our model predicts that (1) positive selection reduces by only 17% the number of T cells that can detect any given foreign peptide, even though it eliminates over 95% of pre-selection cells; (2) negative selection decreases the average cross-reactivity of the pre-selection repertoire by fivefold; and (3) T cells responding to foreign peptides similar to self peptides will have a lower average cross-reactivity than cells responding to epitopes dissimilar to self.
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Affiliation(s)
- Dennis L Chao
- Fred Hutchinson Cancer Research Center, Seattle, USA
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Abstract
Studies of human immunodeficiency virus (HIV) vaccines in animal models suggest that it is difficult to induce complete protection from infection (sterilizing immunity) but that it is possible to reduce the viral load and to slow or prevent disease progression following infection. We have developed an age-structured epidemiological model of the effects of a disease-modifying HIV vaccine that incorporates the intrahost dynamics of infection, a transmission rate and host mortality that depend on the viral load, the possible evolution and transmission of vaccine escape mutant viruses, a finite duration of vaccine protection, and possible changes in sexual behavior. Using this model, we investigated the long-term outcome of a disease-modifying vaccine and utilized uncertainty analysis to quantify the effects of our lack of precise knowledge of various parameters. Our results suggest that the extent of viral load reduction in vaccinated infected individuals (compared to unvaccinated individuals) is the key predictor of vaccine efficacy. Reductions in viral load of about 1 log(10) copies ml(-1) would be sufficient to significantly reduce HIV-associated mortality in the first 20 years after the introduction of vaccination. Changes in sexual risk behavior also had a strong impact on the epidemic outcome. The impact of vaccination is dependent on the population in which it is used, with disease-modifying vaccines predicted to have the most impact in areas of low prevalence and rapid epidemic growth. Surprisingly, the extent to which vaccination alters disease progression, the rate of generation of escape mutants, and the transmission of escape mutants are predicted to have only a weak impact on the epidemic outcome over the first 25 years after the introduction of a vaccine.
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Affiliation(s)
- Miles P Davenport
- Department of Haematology, Prince of Wales Hospital, and Centre for Vascular Research, University of New South Wales, Kensington, NSW, Australia
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Abstract
We have constructed a stochastic stage-structured model of the cytotoxic T lymphocyte (CTL) response to antigen and the maintenance of immunological memory. The model follows the dynamics of a viral infection and the stimulation, proliferation, and differentiation of naïve CD8(+) T cells into effector CTL, which can eliminate virally infected cells. The model is capable of following the dynamics of multiple T cell clones, each with a T cell receptor represented by a digit string. MHC-viral peptide complexes are also represented by strings and a string match rule is used to compute the affinity of a T cell receptor for a viral epitope. The avidities of interactions are also computed by taking into consideration the density of MHC-viral peptides on the surface of an infected cell. Lastly, the model allows the probability of T cell stimulation to depend on avidity but also incorporates the notion of an antigen-independent programmed proliferative response. We compare the model to experimental data on the cytotoxic T cell response to lymphocytic choriomeningitis virus infections.
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Affiliation(s)
- Dennis L Chao
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA
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Abstract
Cytotoxic T lymphocyte (CTL) responses are thought to be important for the control of many viral and other infections. Qualitative aspects of the CTL response, including the epitope specificity, affinity, and clonal composition, may affect the ability of T cells to mediate infection control. Although it is clear that the mode of introduction and the dose of antigen can affect these qualitative aspects of the response, little is understood of the mechanisms. We have developed an in silico model of the CTL response, which we use to study the impact of antigen dose, antigen kinetics and repeated antigen delivery on the response. The results suggest that recent observations on differences in response to killed antigen can be explained simply by differences in timing of T-cell activation. These findings may provide insight into how different vaccination strategies can quantitatively and qualitatively affect the outcome of the immune response.
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Affiliation(s)
- Dennis L Chao
- Department of Computer Science, University of New Mexico, Albuquerque, NM 87131, USA.
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Chao DL, Davenport MP, Forrest S, Perelson AS. Stochastic stage-structured modeling of the adaptive immune system. Proc IEEE Comput Soc Bioinform Conf 2003; 2:124-31. [PMID: 16452786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
We have constructed a computer model of the cytotoxic T lymphocyte (CTL) response to antigen and the maintenance of immunological memory. Because immune responses often begin with small numbers of cells and there is great variation among individual immune systems, we have chosen to implement a stochastic model that captures the life cycle of T cells more faithfully than deterministic models. Past models of the immune response have been differential equation based, which do not capture stochastic effects, or agent-based, which are computationally expensive. We use a stochastic stage-structured approach that has many of the advantages of agent-based modeling but is much more efficient. Our model can provide insights into the effect infections have on the CTL repertoire and the response to subsequent infections.
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Affiliation(s)
- Dennis L Chao
- Department of Computer Science, University of New Mexico, Albuquerque, 87131, USA.
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Lee BK, Chi RC, Chao DL, Cheng J, Chry IY, Beyette FR, Steckl AJ. High-Density Er-Implanted GaN Optical Memory Devices. Appl Opt 2001; 40:3552-3558. [PMID: 18360384 DOI: 10.1364/ao.40.003552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Upconversion emission has been obtained from Er-focused ion-beam (FIB) implanted GaN. Visible green emission at the 522- and 546-nm range were excited with infrared (IR) laser sources at either 840 or 1000 nm, or with both lasers simultaneously. By implanting closely spaced patterns with the FIB, we demonstrated the concept of storing data in Er-implanted GaN. Information stored as data bits consists of patterns of implanted locations as logic 1 and unimplanted locations as logic 0. The photon upconversion process in Er ions is utilized to read the stored information. This process makes use of the IR lasers to excite visible emission. The integrated upconversion emission power was measured to be ~40 pW when pumped by a 840-nm laser at 265 mW and by a 1000-nm laser at 208 mW. Patterns as small as 0.5 mum were implanted and read. Three-dimensional optical memory based on rare-earth-doped semiconductors could in theory approach a storage capacity of 10(12) bits/cm(3).
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Chen MY, Chew EY, Reynolds JC, Chao DL, Oldfield EH. Metastatic brainstem pheochromocytoma in a patient with von Hippel-Lindau disease. Case illustration. J Neurosurg 2001; 94:138. [PMID: 11147885 DOI: 10.3171/jns.2001.94.1.0138] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- M Y Chen
- Surgical Neurology Branch and Department of Nuclear Medicine, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland 20892-1414, USA
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Rak R, Chao DL, Pluta RM, Mitchell JB, Oldfield EH, Watson JC. Neuroprotection by the stable nitroxide Tempol during reperfusion in a rat model of transient focal ischemia. J Neurosurg 2000; 92:646-51. [PMID: 10761655 DOI: 10.3171/jns.2000.92.4.0646] [Citation(s) in RCA: 91] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECT The use of thrombolytic agents in the treatment of stroke has yielded surprisingly modest success, possibly because of reperfusion injury mediated by reactive oxygen species (ROS). Therefore, scavenging ROS may be of therapeutic value in the treatment of stroke. Nitroxides are low-weight superoxide dismutase mimics, which allows them to act as cell-permeable antioxidants. In this study the nitroxide 4-hydroxy-2,2,6,6,-tetramethylpiperidine-1-oxyl (Tempol) is investigated to determine its ability to reduce reperfusion injury. METHODS Male Sprague-Dawley rats weighing between 280 g and 350 g underwent middle cerebral artery occlusion with an intraluminal suture for 60 minutes. Regional cerebral blood flow, blood pressure, cerebral temperature, and rectal temperature were monitored during the procedure. After reperfusion, the animals were randomized to groups receiving blinded intravenous administration of either Tempol (10 mg/kg; eight animals) or vehicle (eight animals) over the first 20 minutes of reperfusion (Study I). In a second study to determine dose dependency, animals were randomized to groups receiving Tempol (20 mg/kg; eight animals), low-dose Tempol (5 mg/kg; eight animals), or vehicle (eight animals; Study II). The rats were killed after 4 hours of reperfusion, and brain sections were stained with 2,3,5 triphenyltetrazolium chloride. Infarct volumes were measured using digital imaging. Animals receiving Tempol had significantly reduced infarct volumes at doses of 20 mg/kg and 10 mg/kg compared with controls (49.01+/-18.22% reduction [p = 0.003] and 47.47+/-34.57 [p = 0.02], respectively). No significant differences in the physiological variables measured were observed between groups. CONCLUSIONS Tempol provides significant neuroprotection after reperfusion in a rat model of transient focal ischemia. These results support the importance of ROS in reperfusion injury and encourage further study of this molecule as a therapeutic agent following thrombolysis.
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Affiliation(s)
- R Rak
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
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Lee SH, Chao DL, Bear JL, Kimball AP. Inhibition of Deamination of Arabinosylcytosine (NSC-63878) by Rhodium(II) Acetate. Cancer Chemother Rep 1975; 59:661-3. [PMID: 1203890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The nobel metal "cage" complex, rhodium(II) acetate, was found to inhibit the deamination of the fraudulent nucleoside, arabinosylcytosine. Potent inhibition of a purified cytidine deaminase from mouse kidney was observed when either cytidine or arabinosylcytosine was used as substrate.
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Chao DL, Kimball AP. Deamination of arabinosyladenine by adenosine deaminase and inhibition by arabinosyl-6-mercaptopurine. Cancer Res 1972; 32:1721-4. [PMID: 5044132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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