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Tedijanto C, Aragie S, Tadesse Z, Haile M, Zeru T, Nash SD, Wittberg DM, Gwyn S, Martin DL, Sturrock HJW, Lietman TM, Keenan JD, Arnold BF. Predicting future community-level ocular Chlamydia trachomatis infection prevalence using serological, clinical, molecular, and geospatial data. PLoS Negl Trop Dis 2022; 16:e0010273. [PMID: 35275911 PMCID: PMC8942265 DOI: 10.1371/journal.pntd.0010273] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 03/23/2022] [Accepted: 02/23/2022] [Indexed: 11/18/2022] Open
Abstract
Trachoma is an infectious disease characterized by repeated exposures to Chlamydia trachomatis (Ct) that may ultimately lead to blindness. Efficient identification of communities with high infection burden could help target more intensive control efforts. We hypothesized that IgG seroprevalence in combination with geospatial layers, machine learning, and model-based geostatistics would be able to accurately predict future community-level ocular Ct infections detected by PCR. We used measurements from 40 communities in the hyperendemic Amhara region of Ethiopia to assess this hypothesis. Median Ct infection prevalence among children 0–5 years old increased from 6% at enrollment, in the context of recent mass drug administration (MDA), to 29% by month 36, following three years without MDA. At baseline, correlation between seroprevalence and Ct infection was stronger among children 0–5 years old (ρ = 0.77) than children 6–9 years old (ρ = 0.48), and stronger than the correlation between active trachoma and Ct infection (0-5y ρ = 0.56; 6-9y ρ = 0.40). Seroprevalence was the strongest concurrent predictor of infection prevalence at month 36 among children 0–5 years old (cross-validated R2 = 0.75, 95% CI: 0.58–0.85), though predictive performance declined substantially with increasing temporal lag between predictor and outcome measurements. Geospatial variables, a spatial Gaussian process, and stacked ensemble machine learning did not meaningfully improve predictions. Serological markers among children 0–5 years old may be an objective tool for identifying communities with high levels of ocular Ct infections, but accurate, future prediction in the context of changing transmission remains an open challenge.
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Affiliation(s)
- Christine Tedijanto
- Francis I. Proctor Foundation, University of California, San Francisco, California, United States of America
- * E-mail:
| | | | | | | | - Taye Zeru
- Amhara Public Health Institute, Bahir Dar, Ethiopia
| | - Scott D. Nash
- The Carter Center, Atlanta, Georgia, United States of America
| | - Dionna M. Wittberg
- Francis I. Proctor Foundation, University of California, San Francisco, California, United States of America
| | - Sarah Gwyn
- Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Diana L. Martin
- Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | | | - Thomas M. Lietman
- Francis I. Proctor Foundation, University of California, San Francisco, California, United States of America
- Department of Ophthalmology, University of California, San Francisco, California, United States of America
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, United States of America
- Institute for Global Health Sciences, University of California, San Francisco, California, United States of America
| | - Jeremy D. Keenan
- Francis I. Proctor Foundation, University of California, San Francisco, California, United States of America
- Department of Ophthalmology, University of California, San Francisco, California, United States of America
| | - Benjamin F. Arnold
- Francis I. Proctor Foundation, University of California, San Francisco, California, United States of America
- Department of Ophthalmology, University of California, San Francisco, California, United States of America
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Abstract
IMPORTANCE Travel distance to abortion services varies widely in the US. Some evidence shows travel distance affects use of abortion care, but there is no national analysis of how abortion rate changes with travel distance. OBJECTIVE To examine the association between travel distance to the nearest abortion care facility and the abortion rate and to model the effect of reduced travel distance. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional geographic analysis used 2015 data on abortions by county of residence from 1948 counties in 27 states. Abortion rates were modeled using a spatial Poisson model adjusted for age, race/ethnicity, marital status, educational attainment, household poverty, nativity, and state abortion policies. Abortion rates for 3107 counties in the 48 contiguous states that were home to 62.5 million female residents of reproductive age (15-44 years) and changes under travel distance scenarios, including integration into primary care (<30 miles) and availability of telemedicine care (<5 miles), were estimated. Data were collected from April 2018 to October 2019 and analyzed from December 2019 to July 2020. EXPOSURES Median travel distance by car to the nearest abortion facility. MAIN OUTCOMES AND MEASURES US county abortion rate per 1000 female residents of reproductive age. RESULTS Among the 1948 counties included in the analysis, greater travel distances were associated with lower abortion rates in a dose-response manner. Compared with a median travel distance of less than 5 miles (median rate, 21.1 [range, 1.2-63.6] per 1000 female residents of reproductive age), distances of 5 to 15 miles (median rate, 12.2 [range, 0.5-23.4] per 1000 female residents of reproductive age; adjusted coefficient, -0.05 [95% CI, -0.07 to -0.03]) and 120 miles or more (median rate, 3.9 [range, 0-12.9] per 1000 female residents of reproductive age; coefficient, -0.73 [95% CI, -0.80 to -0.65]) were associated with lower rates. In a model of 3107 counties with 62.5 million female residents of reproductive age, 696 760 abortions were estimated (mean rate, 11.1 [range, 1.0-45.5] per 1000 female residents of reproductive age). If abortion were integrated into primary care, an additional 18 190 abortions (mean rate, 11.4 [range, 1.1-45.5] per 1000 female residents of reproductive age) were estimated. If telemedicine were widely available, an additional 70 920 abortions were estimated (mean rate, 12.3 [range, 1.4-45.5] per 1000 female residents of reproductive age). CONCLUSIONS AND RELEVANCE These findings suggest that greater travel distances to abortion services are associated with lower abortion rates. The results indicate which geographic areas have insufficient access to abortion care. Modeling suggests that integrating abortion into primary care or making medication abortion care available by telemedicine may decrease unmet need.
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Affiliation(s)
- Kirsten M. J. Thompson
- Bixby Center for Global Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco
| | - Hugh J. W. Sturrock
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Diana Greene Foster
- Advancing New Standards in Reproductive Health, Bixby Center for Global Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco
| | - Ushma D. Upadhyay
- Advancing New Standards in Reproductive Health, Bixby Center for Global Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco
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Hsiang MS, Ntuku H, Roberts KW, Dufour MSK, Whittemore B, Tambo M, McCreesh P, Medzihradsky OF, Prach LM, Siloka G, Siame N, Gueye CS, Schrubbe L, Wu L, Scott V, Tessema S, Greenhouse B, Erlank E, Koekemoer LL, Sturrock HJW, Mwilima A, Katokele S, Uusiku P, Bennett A, Smith JL, Kleinschmidt I, Mumbengegwi D, Gosling R. Effectiveness of reactive focal mass drug administration and reactive focal vector control to reduce malaria transmission in the low malaria-endemic setting of Namibia: a cluster-randomised controlled, open-label, two-by-two factorial design trial. Lancet 2020; 395:1361-1373. [PMID: 32334702 PMCID: PMC7184675 DOI: 10.1016/s0140-6736(20)30470-0] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 01/23/2020] [Accepted: 02/25/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND In low malaria-endemic settings, screening and treatment of individuals in close proximity to index cases, also known as reactive case detection (RACD), is practised for surveillance and response. However, other approaches could be more effective for reducing transmission. We aimed to evaluate the effectiveness of reactive focal mass drug administration (rfMDA) and reactive focal vector control (RAVC) in the low malaria-endemic setting of Zambezi (Namibia). METHODS We did a cluster-randomised controlled, open-label trial using a two-by-two factorial design of 56 enumeration area clusters in the low malaria-endemic setting of Zambezi (Namibia). We randomly assigned these clusters using restricted randomisation to four groups: RACD only, rfMDA only, RAVC plus RACD, or rfMDA plus RAVC. RACD involved rapid diagnostic testing and treatment with artemether-lumefantrine and single-dose primaquine, rfMDA involved presumptive treatment with artemether-lumefantrine, and RAVC involved indoor residual spraying with pirimiphos-methyl. Interventions were administered within 500 m of index cases. To evaluate the effectiveness of interventions targeting the parasite reservoir in humans (rfMDA vs RACD), in mosquitoes (RAVC vs no RAVC), and in both humans and mosquitoes (rfMDA plus RAVC vs RACD only), an intention-to-treat analysis was done. For each of the three comparisons, the primary outcome was the cumulative incidence of locally acquired malaria cases. This trial is registered with ClinicalTrials.gov, number NCT02610400. FINDINGS Between Jan 1, 2017, and Dec 31, 2017, 55 enumeration area clusters had 1118 eligible index cases that led to 342 interventions covering 8948 individuals. The cumulative incidence of locally acquired malaria was 30·8 per 1000 person-years (95% CI 12·8-48·7) in the clusters that received rfMDA versus 38·3 per 1000 person-years (23·0-53·6) in the clusters that received RACD; 30·2 per 1000 person-years (15·0-45·5) in the clusters that received RAVC versus 38·9 per 1000 person-years (20·7-57·1) in the clusters that did not receive RAVC; and 25·0 per 1000 person-years (5·2-44·7) in the clusters that received rfMDA plus RAVC versus 41·4 per 1000 person-years (21·5-61·2) in the clusters that received RACD only. After adjusting for imbalances in baseline and implementation factors, the incidence of malaria was lower in clusters receiving rfMDA than in those receiving RACD (adjusted incidence rate ratio 0·52 [95% CI 0·16-0·88], p=0·009), lower in clusters receiving RAVC than in those that did not (0·48 [0·16-0·80], p=0·002), and lower in clusters that received rfMDA plus RAVC than in those receiving RACD only (0·26 [0·10-0·68], p=0·006). No serious adverse events were reported. INTERPRETATION In a low malaria-endemic setting, rfMDA and RAVC, implemented alone and in combination, reduced malaria transmission and should be considered as alternatives to RACD for elimination of malaria. FUNDING Novartis Foundation, Bill & Melinda Gates Foundation, and Horchow Family Fund.
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Affiliation(s)
- Michelle S Hsiang
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA; Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
| | - Henry Ntuku
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Kathryn W Roberts
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Mi-Suk Kang Dufour
- Division of Prevention Science, University of California San Francisco, San Francisco, CA, USA
| | - Brooke Whittemore
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Munyaradzi Tambo
- Multidisciplinary Research Centre, University of Namibia, Windhoek, Namibia
| | - Patrick McCreesh
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA; Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Oliver F Medzihradsky
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA; Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Lisa M Prach
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Griffith Siloka
- Zambezi Ministry of Health and Social Services, Katima, Namibia
| | - Noel Siame
- Zambezi Ministry of Health and Social Services, Katima, Namibia
| | - Cara Smith Gueye
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Leah Schrubbe
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Lindsey Wu
- Department of Immunology and Infection, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Valerie Scott
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Sofonias Tessema
- Division of Experimental Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Bryan Greenhouse
- Division of Experimental Medicine, Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Erica Erlank
- Wits Research Institute for Malaria, South African Medical Research Council Collaborating Centre for Multi-Disciplinary Research on Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Lizette L Koekemoer
- Wits Research Institute for Malaria, South African Medical Research Council Collaborating Centre for Multi-Disciplinary Research on Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Hugh J W Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Agnes Mwilima
- Zambezi Ministry of Health and Social Services, Katima, Namibia
| | - Stark Katokele
- National Vector-Borne Diseases Control Programme, Namibia Ministry of Health and Social Services, Windhoek, Namibia
| | - Petrina Uusiku
- National Vector-Borne Diseases Control Programme, Namibia Ministry of Health and Social Services, Windhoek, Namibia
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Jennifer L Smith
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA
| | - Immo Kleinschmidt
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Wits Research Institute for Malaria, South African Medical Research Council Collaborating Centre for Multi-Disciplinary Research on Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Southern African Development Community, Malaria Elimination Eight Secretariat, Windhoek, Namibia
| | - Davis Mumbengegwi
- Multidisciplinary Research Centre, University of Namibia, Windhoek, Namibia
| | - Roly Gosling
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, CA, USA; Multidisciplinary Research Centre, University of Namibia, Windhoek, Namibia
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Sturrock AM, Carlson SM, Wikert JD, Heyne T, Nusslé S, Merz JE, Sturrock HJW, Johnson RC. Unnatural selection of salmon life histories in a modified riverscape. Glob Chang Biol 2020; 26:1235-1247. [PMID: 31789453 PMCID: PMC7277499 DOI: 10.1111/gcb.14896] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Accepted: 09/29/2019] [Indexed: 05/26/2023]
Abstract
Altered river flows and fragmented habitats often simplify riverine communities and favor non-native fishes, but their influence on life-history expression and survival is less clear. Here, we quantified the expression and ultimate success of diverse salmon emigration behaviors in an anthropogenically altered California river system. We analyzed two decades of Chinook salmon monitoring data to explore the influence of regulated flows on juvenile emigration phenology, abundance, and recruitment. We then followed seven cohorts into adulthood using otolith (ear stone) chemical archives to identify patterns in time- and size-selective mortality along the migratory corridor. Suppressed winter flow cues were associated with delayed emigration timing, particularly in warm, dry years, which was also when selection against late migrants was the most extreme. Lower, less variable flows were also associated with reduced juvenile and adult production, highlighting the importance of streamflow for cohort success in these southernmost populations. While most juveniles emigrated from the natal stream as fry or smolts, the survivors were dominated by the rare few that left at intermediate sizes and times, coinciding with managed flows released before extreme summer temperatures. The consistent selection against early (small) and late (large) migrants counters prevailing ecological theory that predicts different traits to be favored under varying environmental conditions. Yet, even with this weakened portfolio, maintaining a broad distribution in migration traits still increased adult production and reduced variance. In years exhibiting large fry pulses, even marginal increases in their survival would have significantly boosted recruitment. However, management actions favoring any single phenotype could have negative evolutionary and demographic consequences, potentially reducing adaptability and population stability. To recover fish populations and support viable fisheries in a warming and increasingly unpredictable climate, coordinating flow and habitat management within and among watersheds will be critical to balance trait optimization versus diversification.
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Affiliation(s)
- Anna M. Sturrock
- Center for Watershed SciencesUniversity of California, DavisDavisCAUSA
| | - Stephanie M. Carlson
- Department of Environmental Science, Policy, and ManagementUniversity of California, BerkeleyBerkeleyCAUSA
| | | | - Tim Heyne
- California Department of Fish and WildlifeLa GrangeCAUSA
| | - Sébastien Nusslé
- Department of Environmental Science, Policy, and ManagementUniversity of California, BerkeleyBerkeleyCAUSA
| | - Joseph E. Merz
- Institute of Marine SciencesUniversity of California Santa CruzSanta CruzCAUSA
- Cramer Fish SciencesWest SacramentoCAUSA
| | - Hugh J. W. Sturrock
- Department of Epidemiology & BiostatisticsUniversity of California, San FranciscoSan FranciscoCAUSA
| | - Rachel C. Johnson
- Center for Watershed SciencesUniversity of California, DavisDavisCAUSA
- Fisheries Ecology DivisionSouthwest Fisheries Science CenterNational Marine Fisheries ServiceSanta CruzCAUSA
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Sturrock HJW, Woolheater K, Bennett AF, Andrade-Pacheco R, Midekisa A. Predicting residential structures from open source remotely enumerated data using machine learning. PLoS One 2018; 13:e0204399. [PMID: 30240429 PMCID: PMC6150517 DOI: 10.1371/journal.pone.0204399] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [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: 09/21/2017] [Accepted: 09/09/2018] [Indexed: 11/19/2022] Open
Abstract
Having accurate maps depicting the locations of residential buildings across a region benefits a range of sectors. This is particularly true for public health programs focused on delivering services at the household level, such as indoor residual spraying with insecticide to help prevent malaria. While open source data from OpenStreetMap (OSM) depicting the locations and shapes of buildings is rapidly improving in terms of quality and completeness globally, even in settings where all buildings have been mapped, information on whether these buildings are residential, commercial or another type is often only available for a small subset. Using OSM building data from Botswana and Swaziland, we identified buildings for which 'type' was indicated, generated via on the ground observations, and classified these into two classes, "sprayable" and "not-sprayable". Ensemble machine learning, using building characteristics such as size, shape and proximity to neighbouring features, was then used to form a model to predict which of these 2 classes every building in these two countries fell into. Results show that an ensemble machine learning approach performed marginally, but statistically, better than the best individual model and that using this ensemble model we were able to correctly classify >86% (using independent test data) of structures correctly as sprayable and not-sprayable across both countries.
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Affiliation(s)
- Hugh J. W. Sturrock
- Global Health Group, University of California, San Francisco, CA, United States of America
| | | | - Adam F. Bennett
- Global Health Group, University of California, San Francisco, CA, United States of America
| | | | - Alemayehu Midekisa
- Global Health Group, University of California, San Francisco, CA, United States of America
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Knowles SCL, Sturrock HJW, Turner H, Whitton JM, Gower CM, Jemu S, Phillips AE, Meite A, Thomas B, Kollie K, Thomas C, Rebollo MP, Styles B, Clements M, Fenwick A, Harrison WE, Fleming FM. Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. PLoS Negl Trop Dis 2017; 11:e0005599. [PMID: 28552961 PMCID: PMC5464666 DOI: 10.1371/journal.pntd.0005599] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [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: 10/05/2016] [Revised: 06/08/2017] [Accepted: 04/26/2017] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated. METHODOLOGY/PRINCIPAL FINDINGS We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district. CONCLUSIONS/SIGNIFICANCE Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose.
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Affiliation(s)
- Sarah C. L. Knowles
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- The Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- * E-mail:
| | - Hugh J. W. Sturrock
- Global Health Group, University of California San Francisco, San Francisco, California, United States of America
| | - Hugo Turner
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
| | - Jane M. Whitton
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
| | - Charlotte M. Gower
- The Royal Veterinary College, Hawkshead Lane, Hatfield, Hertfordshire, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
- Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
| | - Samuel Jemu
- Ministry of Health, Capital City, Lilongwe 3, Malawi
| | - Anna E. Phillips
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
| | - Aboulaye Meite
- Ministry of Health and Social Welfare of Côte d’Ivoire, Abidjan, Côte d’Ivoire
| | - Brent Thomas
- Fliarial Programme Support Unit, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, United Kingdom
| | - Karsor Kollie
- Neglected Tropical and Non Communicable Diseases Program, Ministry of Health and Social Welfare, Monrovia 10, Liberia
| | - Catherine Thomas
- Neglected Tropical and Non Communicable Diseases Program, Ministry of Health and Social Welfare, Monrovia 10, Liberia
| | - Maria P. Rebollo
- Fliarial Programme Support Unit, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, United Kingdom
| | - Ben Styles
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- National Foundation for Educational Research, Upton Park, Slough, United Kingdom
| | - Michelle Clements
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
| | - Alan Fenwick
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
| | - Wendy E. Harrison
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
| | - Fiona M. Fleming
- Schistosomiasis Control Initiative, Department of Infectious Disease Epidemiology, Imperial College London, St. Mary’s Campus, Norfolk Place, London, United Kingdom
- London Centre for Neglected Tropical Disease Research, London, United Kingdom
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Smith JL, Auala J, Haindongo E, Uusiku P, Gosling R, Kleinschmidt I, Mumbengegwi D, Sturrock HJW. Malaria risk in young male travellers but local transmission persists: a case-control study in low transmission Namibia. Malar J 2017; 16:70. [PMID: 28187770 PMCID: PMC5303241 DOI: 10.1186/s12936-017-1719-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Accepted: 02/03/2017] [Indexed: 11/24/2022] Open
Abstract
Background A key component of malaria elimination campaigns is the identification and targeting of high risk populations. To characterize high risk populations in north central Namibia, a prospective health facility-based case–control study was conducted from December 2012–July 2014. Cases (n = 107) were all patients presenting to any of the 46 health clinics located in the study districts with a confirmed Plasmodium infection by multi-species rapid diagnostic test (RDT). Population controls (n = 679) for each district were RDT negative individuals residing within a household that was randomly selected from a census listing using a two-stage sampling procedure. Demographic, travel, socio-economic, behavioural, climate and vegetation data were also collected. Spatial patterns of malaria risk were analysed. Multivariate logistic regression was used to identify risk factors for malaria. Results Malaria risk was observed to cluster along the border with Angola, and travel patterns among cases were comparatively restricted to northern Namibia and Angola. Travel to Angola was associated with excessive risk of malaria in males (OR 43.58 95% CI 2.12–896), but there was no corresponding risk associated with travel by females. This is the first study to reveal that gender can modify the effect of travel on risk of malaria. Amongst non-travellers, male gender was also associated with a higher risk of malaria compared with females (OR 1.95 95% CI 1.25–3.04). Other strong risk factors were sleeping away from the household the previous night, lower socioeconomic status, living in an area with moderate vegetation around their house, experiencing moderate rainfall in the month prior to diagnosis and living <15 km from the Angolan border. Conclusions These findings highlight the critical need to target malaria interventions to young male travellers, who have a disproportionate risk of malaria in northern Namibia, to coordinate cross-border regional malaria prevention initiatives and to scale up coverage of prevention measures such as indoor residual spraying and long-lasting insecticide nets in high risk areas if malaria elimination is to be realized. Electronic supplementary material The online version of this article (doi:10.1186/s12936-017-1719-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jennifer L Smith
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, CA, USA.
| | - Joyce Auala
- Multidisciplinary Research Center, University of Namibia, Windhoek, Namibia
| | - Erastus Haindongo
- Multidisciplinary Research Center, University of Namibia, Windhoek, Namibia
| | - Petrina Uusiku
- National Vector-Borne Disease Control Programme, Ministry of Health and Social Services, Windhoek, Namibia
| | - Roly Gosling
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, CA, USA
| | - Immo Kleinschmidt
- MRC Tropical Epidemiology Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Davis Mumbengegwi
- Multidisciplinary Research Center, University of Namibia, Windhoek, Namibia
| | - Hugh J W Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, CA, USA
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8
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Parizo J, Sturrock HJW, Dhiman RC, Greenhouse B. Spatiotemporal Analysis of Malaria in Urban Ahmedabad (Gujarat), India: Identification of Hot Spots and Risk Factors for Targeted Intervention. Am J Trop Med Hyg 2016; 95:595-603. [PMID: 27382081 DOI: 10.4269/ajtmh.16-0108] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 05/07/2016] [Indexed: 11/07/2022] Open
Abstract
The world population, especially in developing countries, has experienced a rapid progression of urbanization over the last half century. Urbanization has been accompanied by a rise in cases of urban infectious diseases, such as malaria. The complexity and heterogeneity of the urban environment has made study of specific urban centers vital for urban malaria control programs, whereas more generalizable risk factor identification also remains essential. Ahmedabad city, India, is a large urban center located in the state of Gujarat, which has experienced a significant Plasmodium vivax and Plasmodium falciparum disease burden. Therefore, a targeted analysis of malaria in Ahmedabad city was undertaken to identify spatiotemporal patterns of malaria, risk factors, and methods of predicting future malaria cases. Malaria incidence in Ahmedabad city was found to be spatially heterogeneous, but temporally stable, with high spatial correlation between species. Because of this stability, a prediction method utilizing historic cases from prior years and seasons was used successfully to predict which areas of Ahmedabad city would experience the highest malaria burden and could be used to prospectively target interventions. Finally, spatial analysis showed that normalized difference vegetation index, proximity to water sources, and location within Ahmedabad city relative to the dense urban core were the best predictors of malaria incidence. Because of the heterogeneity of urban environments and urban malaria itself, the study of specific large urban centers is vital to assist in allocating resources and informing future urban planning.
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Affiliation(s)
- Justin Parizo
- Department of Medicine, Stanford University Medical Center, Palo Alto, California
| | - Hugh J W Sturrock
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California
| | - Ramesh C Dhiman
- National Institute of Malaria Research (Indian Council of Medical Research), New Delhi, India.
| | - Bryan Greenhouse
- Division of Infectious Diseases, Department of Medicine, University of California San Francisco, San Francisco, California
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9
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Ren Z, Wang D, Ma A, Hwang J, Bennett A, Sturrock HJW, Fan J, Zhang W, Yang D, Feng X, Xia Z, Zhou XN, Wang J. Predicting malaria vector distribution under climate change scenarios in China: Challenges for malaria elimination. Sci Rep 2016; 6:20604. [PMID: 26868185 PMCID: PMC4751525 DOI: 10.1038/srep20604] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2014] [Accepted: 01/08/2016] [Indexed: 01/19/2023] Open
Abstract
Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.
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Affiliation(s)
- Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Duoquan Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.,World Health Organization Collaborating Centre for Tropical Diseases, Shanghai, China.,National Center for International Research on Tropical Diseases, Shanghai, China
| | - Aimin Ma
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China.,College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
| | - Jimee Hwang
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America.,President's Malaria Initiative, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, United States of America
| | - Adam Bennett
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Hugh J W Sturrock
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Junfu Fan
- School of Civil and Architectural Engineering, Shandong University of Technology, Zibo, China
| | - Wenjie Zhang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dian Yang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xinyu Feng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.,World Health Organization Collaborating Centre for Tropical Diseases, Shanghai, China.,National Center for International Research on Tropical Diseases, Shanghai, China
| | - Zhigui Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.,World Health Organization Collaborating Centre for Tropical Diseases, Shanghai, China.,National Center for International Research on Tropical Diseases, Shanghai, China
| | - Xiao-Nong Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China.,World Health Organization Collaborating Centre for Tropical Diseases, Shanghai, China.,National Center for International Research on Tropical Diseases, Shanghai, China
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing 100101, China.,Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China.,Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
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10
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Sturrock HJW, Roberts KW, Wegbreit J, Ohrt C, Gosling RD. Tackling imported malaria: an elimination endgame. Am J Trop Med Hyg 2015; 93:139-144. [PMID: 26013369 PMCID: PMC4497886 DOI: 10.4269/ajtmh.14-0256] [Citation(s) in RCA: 68] [Impact Index Per Article: 7.6] [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] [Received: 04/25/2014] [Accepted: 02/01/2015] [Indexed: 12/31/2022] Open
Abstract
As countries move toward malaria elimination, imported infections become increasingly significant as they often represent the majority of cases, can sustain transmission, cause resurgences, and lead to mortality. Here we review and critique current methods to prevent malaria importation in countries pursuing elimination and explore methods applied in other transmission settings and to other diseases that could be transferred to support malaria elimination. To improve intervention targeting we need a better understanding of the characteristics of populations importing infections and their patterns of migration, improved methods to reliably classify infections as imported or acquired locally, and ensure early and accurate diagnosis. The potential for onward transmission in the most receptive and vulnerable locations can be predicted through high-resolution risk mapping that can help malaria elimination or prevention of reintroduction programs target resources. Cross border and regional initiatives can be highly effective when based on an understanding of human and parasite movement. Ultimately, determining the optimal combinations of approaches to address malaria importation will require an evaluation of their impact, cost effectiveness, and operational feasibility.
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Affiliation(s)
- Hugh J. W. Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, California
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11
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Ohrt C, Roberts KW, Sturrock HJW, Wegbreit J, Lee BY, Gosling RD. Information systems to support surveillance for malaria elimination. Am J Trop Med Hyg 2015; 93:145-152. [PMID: 26013378 PMCID: PMC4497887 DOI: 10.4269/ajtmh.14-0257] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [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] [Received: 04/25/2014] [Accepted: 04/13/2015] [Indexed: 11/07/2022] Open
Abstract
Robust and responsive surveillance systems are critical for malaria elimination. The ideal information system that supports malaria elimination includes: rapid and complete case reporting, incorporation of related data, such as census or health survey information, central data storage and management, automated and expert data analysis, and customized outputs and feedback that lead to timely and targeted responses. Spatial information enhances such a system, ensuring cases are tracked and mapped over time. Data sharing and coordination across borders are vital and new technologies can improve data speed, accuracy, and quality. Parts of this ideal information system exist and are in use, but have yet to be linked together coherently. Malaria elimination programs should support the implementation and refinement of information systems to support surveillance and response and ensure political and financial commitment to maintain the systems and the human resources needed to run them. National malaria programs should strive to improve the access and utility of these information systems and establish cross-border data sharing mechanisms through the use of standard indicators for malaria surveillance. Ultimately, investment in the information technologies that support a timely and targeted surveillance and response system is essential for malaria elimination.
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Affiliation(s)
- Colin Ohrt
- *Address correspondence to Colin Ohrt, Malaria Elimination Initiative, Global Health Group, University of California, National Institute for Malariology, Parasitology and Entomology, 35 Trung Van Road, Tu Liem, Hanoi, Vietnam. E-mails: or
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12
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Ren Z, Wang D, Hwang J, Bennett A, Sturrock HJW, Ma A, Huang J, Xia Z, Feng X, Wang J. Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China. PLoS One 2015; 10:e0116932. [PMID: 25611483 PMCID: PMC4303435 DOI: 10.1371/journal.pone.0116932] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [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] [Received: 07/01/2014] [Accepted: 11/26/2014] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Robust malaria vector surveillance is essential for optimally selecting and targeting vector control measures. Sixty-two vector surveillance sites were established between 2005 and 2008 by the national malaria surveillance program in China to measure Anopheles sinensis human biting rates. Using these data to determine the primary ecological drivers of malaria vector human biting rates in malaria epidemic-prone regions of China will allow better targeting of vector control resources in space and time as the country aims to eliminate malaria. METHODS We analyzed data from 62 malaria surveillance sentinel sites from 2005 to 2008. Linear mixed effects models were used to identify the primary ecological drivers for Anopheles sinensis human biting rates as well as to explore the spatial-temporal variation of relevant factors at surveillance sites throughout China. RESULTS Minimum semimonthly temperature (β = 2.99; 95% confidence interval (CI) 2.07- 3.92), enhanced vegetation index (β =1.07; 95% CI 0.11-2.03), and paddy index (the percentage of rice paddy field in the total cultivated land area of each site) (β = 0.86; 95% CI 0.17-1.56) were associated with greater An. Sinensis human biting rates, while increasing distance to the nearest river was associated with lower An. Sinensis human biting rates (β = -1.47; 95% CI -2.88, -0.06). The temporal variation (σ(s0)(2) = 0.83) in biting rates was much larger than the spatial variation (σ(t)(2) = 1.35), with 19.3% of temporal variation attributable to differences in minimum temperature and enhanced vegetation index and 16.9% of spatial variance due to distance to the nearest river and the paddy index. DISCUSSION Substantial spatial-temporal variation in An. Sinensis human biting rates exists in malaria epidemic-prone regions of China, with minimum temperature and enhanced vegetation index accounting for the greatest proportion of temporal variation and distance to nearest river and paddy index accounting for the greatest proportion of spatial variation amongst observed ecological drivers. CONCLUSIONS Targeted vector control measures based on these findings can support the ongoing malaria elimination efforts in China more effectively.
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Affiliation(s)
- Zhoupeng Ren
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Duoquan Wang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Jimee Hwang
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
- Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
| | - Adam Bennett
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
| | - Hugh J. W. Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California San Francisco, San Francisco, California, United States of America
| | - Aimin Ma
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, China
| | - Jixia Huang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
- Center of 3S Technology and Mapping, Beijing Forestry University, Beijing, China
| | - Zhigui Xia
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Xinyu Feng
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, WHO Collaborating Center for Malaria, Schistosomiasis and Filariasis, Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, People’s Republic of China
| | - Jinfeng Wang
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Science and Natural Resource Research, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
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13
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Smith JL, Sturrock HJW, Assefa L, Nikolay B, Njenga SM, Kihara J, Mwandawiro CS, Brooker SJ. Factors associated with the performance and cost-effectiveness of using lymphatic filariasis transmission assessment surveys for monitoring soil-transmitted helminths: a case study in Kenya. Am J Trop Med Hyg 2014; 92:342-353. [PMID: 25487730 PMCID: PMC4347340 DOI: 10.4269/ajtmh.14-0435] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [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: 01/24/2023] Open
Abstract
Transmission assessment surveys (TAS) for lymphatic filariasis have been proposed as a platform to assess the impact of mass drug administration (MDA) on soil-transmitted helminths (STHs). This study used computer simulation and field data from pre- and post-MDA settings across Kenya to evaluate the performance and cost-effectiveness of the TAS design for STH assessment compared with alternative survey designs. Variations in the TAS design and different sample sizes and diagnostic methods were also evaluated. The district-level TAS design correctly classified more districts compared with standard STH designs in pre-MDA settings. Aggregating districts into larger evaluation units in a TAS design decreased performance, whereas age group sampled and sample size had minimal impact. The low diagnostic sensitivity of Kato-Katz and mini-FLOTAC methods was found to increase misclassification. We recommend using a district-level TAS among children 8-10 years of age to assess STH but suggest that key consideration is given to evaluation unit size.
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Affiliation(s)
- Jennifer L. Smith
- *Address correspondence to Jennifer L. Smith, Global Health Group, University of California San Francisco, 50 Beale Street, San Francisco, CA 94105. E-mail:
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14
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Mosha JF, Sturrock HJW, Brown JM, Hashim R, Kibiki G, Chandramohan D, Gosling RD. The independent effect of living in malaria hotspots on future malaria infection: an observational study from Misungwi, Tanzania. Malar J 2014; 13:445. [PMID: 25413016 PMCID: PMC4255924 DOI: 10.1186/1475-2875-13-445] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Accepted: 11/10/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND As malaria transmission declines, continued improvements of prevention and control interventions will increasingly rely on accurate knowledge of risk factors and an ability to define high-risk areas and populations at risk for focal targeting of interventions. This paper explores the independent association between living in a hotspot and prospective risk of malaria infection. METHODS Malaria infection status defined by nPCR and AMA-1 status in year 1 were used to define geographic hotspots using two geospatial statistical methods (SaTScan and Kernel density smoothing). Other malaria risk factors for malaria infection were explored by fitting a multivariable model. RESULTS This study demonstrated that residing in infection hotspot of malaria transmission is an independent predictor of malaria infection in the future. CONCLUSION It is likely that targeting such hotspots with better coverage and improved malaria control strategies will result in more cost-efficient uses of resources to move towards malaria elimination.
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Affiliation(s)
- Jacklin F Mosha
- National Institute for Medical Research (NIMR), Mwanza Medical Research Centre, Mwanza, Tanzania.
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15
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Sturrock HJW, Cohen JM, Keil P, Tatem AJ, Le Menach A, Ntshalintshali NE, Hsiang MS, Gosling RD. Fine-scale malaria risk mapping from routine aggregated case data. Malar J 2014; 13:421. [PMID: 25366929 PMCID: PMC4349235 DOI: 10.1186/1475-2875-13-421] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2014] [Accepted: 10/25/2014] [Indexed: 11/22/2022] Open
Abstract
Background Mapping malaria risk is an integral component of efficient resource allocation. Routine health facility data are convenient to collect, but without information on the locations at which transmission occurred, their utility for predicting variation in risk at a sub-catchment level is presently unclear. Methods Using routinely collected health facility level case data in Swaziland between 2011–2013, and fine scale environmental and ecological variables, this study explores the use of a hierarchical Bayesian modelling framework for downscaling risk maps from health facility catchment level to a fine scale (1 km x 1 km). Fine scale predictions were validated using known household locations of cases and a random sample of points to act as pseudo-controls. Results Results show that fine-scale predictions were able to discriminate between cases and pseudo-controls with an AUC value of 0.84. When scaled up to catchment level, predicted numbers of cases per health facility showed broad correspondence with observed numbers of cases with little bias, with 84 of the 101 health facilities with zero cases correctly predicted as having zero cases. Conclusions This method holds promise for helping countries in pre-elimination and elimination stages use health facility level data to produce accurate risk maps at finer scales. Further validation in other transmission settings and an evaluation of the operational value of the approach is necessary. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-13-421) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hugh J W Sturrock
- Global Health Group, University of California, San Francisco, SF, USA.
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16
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Cao J, Sturrock HJW, Cotter C, Zhou S, Zhou H, Liu Y, Tang L, Gosling RD, Feachem RGA, Gao Q. Communicating and monitoring surveillance and response activities for malaria elimination: China's "1-3-7" strategy. PLoS Med 2014; 11:e1001642. [PMID: 24824170 PMCID: PMC4019513 DOI: 10.1371/journal.pmed.1001642] [Citation(s) in RCA: 143] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Qi Gao and colleagues describe China's 1-3-7 strategy for eliminating malaria: reporting of malaria cases within one day, their confirmation and investigation within three days, and the appropriate public health response to prevent further transmission within seven days.
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Affiliation(s)
- Jun Cao
- Jiangsu Institute of Parasitic Diseases, Wuxi, China; Key Laboratory of Parasitic Disease Control and Prevention, Ministry of Health, Wuxi, China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China
| | - Hugh J W Sturrock
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Chris Cotter
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Shuisen Zhou
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Huayun Zhou
- Jiangsu Institute of Parasitic Diseases, Wuxi, China; Key Laboratory of Parasitic Disease Control and Prevention, Ministry of Health, Wuxi, China
| | - Yaobao Liu
- Jiangsu Institute of Parasitic Diseases, Wuxi, China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China
| | - Linhua Tang
- National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, Shanghai, China
| | - Roly D Gosling
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Richard G A Feachem
- Global Health Group, University of California, San Francisco, San Francisco, California, United States of America
| | - Qi Gao
- Jiangsu Institute of Parasitic Diseases, Wuxi, China; Key Laboratory of Parasitic Disease Control and Prevention, Ministry of Health, Wuxi, China; Jiangsu Provincial Key Laboratory of Parasite Molecular Biology, Wuxi, China
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17
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Mosha JF, Sturrock HJW, Greenwood B, Sutherland CJ, Gadalla NB, Atwal S, Hemelaar S, Brown JM, Drakeley C, Kibiki G, Bousema T, Chandramohan D, Gosling RD. Hot spot or not: a comparison of spatial statistical methods to predict prospective malaria infections. Malar J 2014; 13:53. [PMID: 24517452 PMCID: PMC3932034 DOI: 10.1186/1475-2875-13-53] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2013] [Accepted: 02/06/2014] [Indexed: 12/02/2022] Open
Abstract
Background Within affected communities, Plasmodium falciparum infections may be skewed in distribution such that single or small clusters of households consistently harbour a disproportionate number of infected individuals throughout the year. Identifying these hotspots of malaria transmission would permit targeting of interventions and a more rapid reduction in malaria burden across the whole community. This study set out to compare different statistical methods of hotspot detection (SaTScan, kernel smoothing, weighted local prevalence) using different indicators (PCR positivity, AMA-1 and MSP-1 antibodies) for prediction of infection the following year. Methods Two full surveys of four villages in Mwanza, Tanzania were completed over consecutive years, 2010-2011. In both surveys, infection was assessed using nested polymerase chain reaction (nPCR). In addition in 2010, serologic markers (AMA-1 and MSP-119 antibodies) of exposure were assessed. Baseline clustering of infection and serological markers were assessed using three geospatial methods: spatial scan statistics, kernel analysis and weighted local prevalence analysis. Methods were compared in their ability to predict infection in the second year of the study using random effects logistic regression models, and comparisons of the area under the receiver operating curve (AUC) for each model. Sensitivity analysis was conducted to explore the effect of varying radius size for the kernel and weighted local prevalence methods and maximum population size for the spatial scan statistic. Results Guided by AUC values, the kernel method and spatial scan statistics appeared to be more predictive of infection in the following year. Hotspots of PCR-detected infection and seropositivity to AMA-1 were predictive of subsequent infection. For the kernel method, a 1 km window was optimal. Similarly, allowing hotspots to contain up to 50% of the population was a better predictor of infection in the second year using spatial scan statistics than smaller maximum population sizes. Conclusions Clusters of AMA-1 seroprevalence or parasite prevalence that are predictive of infection a year later can be identified using geospatial models. Kernel smoothing using a 1 km window and spatial scan statistics both provided accurate prediction of future infection.
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Affiliation(s)
- Jacklin F Mosha
- National Institute for Medical Research (NIMR), Mwanza Medical Research Centre, Mwanza, Tanzania.
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18
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Cotter C, Sturrock HJW, Hsiang MS, Liu J, Phillips AA, Hwang J, Gueye CS, Fullman N, Gosling RD, Feachem RGA. The changing epidemiology of malaria elimination: new strategies for new challenges. Lancet 2013; 382:900-11. [PMID: 23594387 PMCID: PMC10583787 DOI: 10.1016/s0140-6736(13)60310-4] [Citation(s) in RCA: 440] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Malaria-eliminating countries achieved remarkable success in reducing their malaria burdens between 2000 and 2010. As a result, the epidemiology of malaria in these settings has become more complex. Malaria is increasingly imported, caused by Plasmodium vivax in settings outside sub-Saharan Africa, and clustered in small geographical areas or clustered demographically into subpopulations, which are often predominantly adult men, with shared social, behavioural, and geographical risk characteristics. The shift in the populations most at risk of malaria raises important questions for malaria-eliminating countries, since traditional control interventions are likely to be less effective. Approaches to elimination need to be aligned with these changes through the development and adoption of novel strategies and methods. Knowledge of the changing epidemiological trends of malaria in the eliminating countries will ensure improved targeting of interventions to continue to shrink the malaria map.
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Affiliation(s)
- Chris Cotter
- The Global Health Group, University of California, San Francisco, CA 94105, USA.
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19
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Smith JL, Sturrock HJW, Olives C, Solomon AW, Brooker SJ. Comparing the performance of cluster random sampling and integrated threshold mapping for targeting trachoma control, using computer simulation. PLoS Negl Trop Dis 2013; 7:e2389. [PMID: 23991238 PMCID: PMC3749968 DOI: 10.1371/journal.pntd.0002389] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [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: 02/19/2013] [Accepted: 07/17/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Implementation of trachoma control strategies requires reliable district-level estimates of trachomatous inflammation-follicular (TF), generally collected using the recommended gold-standard cluster randomized surveys (CRS). Integrated Threshold Mapping (ITM) has been proposed as an integrated and cost-effective means of rapidly surveying trachoma in order to classify districts according to treatment thresholds. ITM differs from CRS in a number of important ways, including the use of a school-based sampling platform for children aged 1-9 and a different age distribution of participants. This study uses computerised sampling simulations to compare the performance of these survey designs and evaluate the impact of varying key parameters. METHODOLOGY/PRINCIPAL FINDINGS Realistic pseudo gold standard data for 100 districts were generated that maintained the relative risk of disease between important sub-groups and incorporated empirical estimates of disease clustering at the household, village and district level. To simulate the different sampling approaches, 20 clusters were selected from each district, with individuals sampled according to the protocol for ITM and CRS. Results showed that ITM generally under-estimated the true prevalence of TF over a range of epidemiological settings and introduced more district misclassification according to treatment thresholds than did CRS. However, the extent of underestimation and resulting misclassification was found to be dependent on three main factors: (i) the district prevalence of TF; (ii) the relative risk of TF between enrolled and non-enrolled children within clusters; and (iii) the enrollment rate in schools. CONCLUSIONS/SIGNIFICANCE Although in some contexts the two methodologies may be equivalent, ITM can introduce a bias-dependent shift as prevalence of TF increases, resulting in a greater risk of misclassification around treatment thresholds. In addition to strengthening the evidence base around choice of trachoma survey methodologies, this study illustrates the use of a simulated approach in addressing operational research questions for trachoma but also other NTDs.
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Affiliation(s)
- Jennifer L Smith
- London School of Hygiene and Tropical Medicine, London, United Kingdom.
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Mosha JF, Sturrock HJW, Greenhouse B, Greenwood B, Sutherland CJ, Gadalla N, Atwal S, Drakeley C, Kibiki G, Bousema T, Chandramohan D, Gosling R. Epidemiology of subpatent Plasmodium falciparum infection: implications for detection of hotspots with imperfect diagnostics. Malar J 2013; 12:221. [PMID: 23815811 PMCID: PMC3701503 DOI: 10.1186/1475-2875-12-221] [Citation(s) in RCA: 87] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2013] [Accepted: 06/26/2013] [Indexed: 01/28/2023] Open
Abstract
Background At the local level, malaria transmission clusters in hotspots, which may be a group of households that experience higher than average exposure to infectious mosquitoes. Active case detection often relying on rapid diagnostic tests for mass screen and treat campaigns has been proposed as a method to detect and treat individuals in hotspots. Data from a cross-sectional survey conducted in north-western Tanzania were used to examine the spatial distribution of Plasmodium falciparum and the relationship between household exposure and parasite density. Methods Dried blood spots were collected from consenting individuals from four villages during a survey conducted in 2010. These were analysed by PCR for the presence of P. falciparum, with the parasite density of positive samples being estimated by quantitative PCR. Household exposure was estimated using the distance-weighted PCR prevalence of infection. Parasite density simulations were used to estimate the proportion of infections that would be treated using a screen and treat approach with rapid diagnostic tests (RDT) compared to targeted mass drug administration (tMDA) and Mass Drug Administration (MDA). Results Polymerase chain reaction PCR analysis revealed that of the 3,057 blood samples analysed, 1,078 were positive. Mean distance-weighted PCR prevalence per household was 34.5%. Parasite density was negatively associated with transmission intensity with the odds of an infection being subpatent increasing with household exposure (OR 1.09 per 1% increase in exposure). Parasite density was also related to age, being highest in children five to ten years old and lowest in those > 40 years. Simulations of different tMDA strategies showed that treating all individuals in households where RDT prevalence was above 20% increased the number of infections that would have been treated from 43 to 55%. However, even with this strategy, 45% of infections remained untreated. Conclusion The negative relationship between household exposure and parasite density suggests that DNA-based detection of parasites is needed to provide adequate sensitivity in hotspots. Targeting MDA only to households with RDT-positive individuals may allow a larger fraction of infections to be treated. These results suggest that community-wide MDA, instead of screen and treat strategies, may be needed to successfully treat the asymptomatic, subpatent parasite reservoir and reduce transmission in similar settings.
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Affiliation(s)
- Jacklin F Mosha
- National Institute for Medical Research, NIMR, Mwanza Medical Research Centre, Mwanza, Tanzania.
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Abstract
Hugh Sturrock and colleagues discuss the role of active case detection in low malaria transmission settings. They argue that the evidence for its effectiveness is sparse and that targeted mass drug administration should be evaluated as an alternative or addition to active case detection. Please see later in the article for the Editors' Summary
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Affiliation(s)
- Hugh J W Sturrock
- Malaria Elimination Initiative, Global Health Group, University of California, San Francisco, USA.
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Pullan RL, Sturrock HJW, Soares Magalhães RJ, Clements ACA, Brooker SJ. Spatial parasite ecology and epidemiology: a review of methods and applications. Parasitology 2012; 139:1870-87. [PMID: 23036435 PMCID: PMC3526959 DOI: 10.1017/s0031182012000698] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [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: 01/13/2012] [Revised: 03/11/2012] [Accepted: 04/03/2012] [Indexed: 12/21/2022]
Abstract
The distributions of parasitic diseases are determined by complex factors, including many that are distributed in space. A variety of statistical methods are now readily accessible to researchers providing opportunities for describing and ultimately understanding and predicting spatial distributions. This review provides an overview of the spatial statistical methods available to parasitologists, ecologists and epidemiologists and discusses how such methods have yielded new insights into the ecology and epidemiology of infection and disease. The review is structured according to the three major branches of spatial statistics: continuous spatial variation; discrete spatial variation; and spatial point processes.
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Edwards T, Smith J, Sturrock HJW, Kur LW, Sabasio A, Finn TP, Lado M, Haddad D, Kolaczinski JH. Prevalence of trachoma in unity state, South Sudan: results from a large-scale population-based survey and potential implications for further surveys. PLoS Negl Trop Dis 2012; 6:e1585. [PMID: 22506082 PMCID: PMC3323519 DOI: 10.1371/journal.pntd.0001585] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [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: 08/27/2011] [Accepted: 02/07/2012] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Large parts of South Sudan are thought to be trachoma-endemic but baseline data are limited. This study aimed to estimate prevalence for planning trachoma interventions in Unity State, to identify risk factors and to investigate the effect of different sampling approaches on study conclusions. METHODS AND FINDINGS The survey area was defined as one domain of eight counties in Unity State. Across the area, 40 clusters (villages) were randomly selected proportional to the county population size in a population-based prevalence survey. The simplified grading scheme was used to classify clinical signs of trachoma. The unadjusted prevalence of trachoma inflammation-follicular (TF) in children aged 1-9 years was 70.5% (95% CI: 68.6-72.3). After adjusting for age, sex, county and clustering of cases at household and village level the prevalence was 71.0% (95% CI: 69.9-72.1). The prevalence of trachomatous trichiasis (TT) in adults was 15.1% (95% CI: 13.4-17.0) and 13.5% (95% CI: 12.0-15.1) before and after adjustment, respectively. We estimate that 700,000 people (the entire population of Unity State) require antibiotic treatment and approximately 54,178 people require TT surgery. Risk factor analyses confirmed child-level associations with TF and highlighted that older adults living in poverty are at higher risk of TT. Conditional simulations, testing the alternatives of sampling 20 or 60 villages over the same area, indicated that sampling of only 20 villages would have provided an acceptable level of precision for state-level prevalence estimation to inform intervention decisions in this hyperendemic setting. CONCLUSION Trachoma poses an enormous burden on the population of Unity State. Comprehensive control is urgently required to avoid preventable blindness and should be initiated across the state now. In other parts of South Sudan suspected to be highly trachoma endemic, counties should be combined into larger survey areas to generate the baseline data required to initiate interventions.
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Affiliation(s)
- Tansy Edwards
- Medical Research Council Tropical Epidemiology Group, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jennifer Smith
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Hugh J. W. Sturrock
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Lucia W. Kur
- Ministry of Health, Juba, Republic of South Sudan
| | - Anthony Sabasio
- Malaria Consortium South Sudan, Juba, Republic of South Sudan
| | - Timothy P. Finn
- Malaria Consortium South Sudan, Juba, Republic of South Sudan
| | - Mounir Lado
- Ministry of Health, Juba, Republic of South Sudan
| | - Danny Haddad
- International Trachoma Initiative, Decatur, Georgia, United States of America
| | - Jan H. Kolaczinski
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Malaria Consortium Africa Regional Office, Kampala, Uganda
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Pullan RL, Gething PW, Smith JL, Mwandawiro CS, Sturrock HJW, Gitonga CW, Hay SI, Brooker S. Spatial modelling of soil-transmitted helminth infections in Kenya: a disease control planning tool. PLoS Negl Trop Dis 2011; 5:e958. [PMID: 21347451 PMCID: PMC3035671 DOI: 10.1371/journal.pntd.0000958] [Citation(s) in RCA: 93] [Impact Index Per Article: 7.2] [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: 07/28/2010] [Accepted: 01/07/2011] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Implementation of control of parasitic diseases requires accurate, contemporary maps that provide intervention recommendations at policy-relevant spatial scales. To guide control of soil transmitted helminths (STHs), maps are required of the combined prevalence of infection, indicating where this prevalence exceeds an intervention threshold of 20%. Here we present a new approach for mapping the observed prevalence of STHs, using the example of Kenya in 2009. METHODS AND FINDINGS Observed prevalence data for hookworm, Ascaris lumbricoides and Trichuris trichiura were assembled for 106,370 individuals from 945 cross-sectional surveys undertaken between 1974 and 2009. Ecological and climatic covariates were extracted from high-resolution satellite data and matched to survey locations. Bayesian space-time geostatistical models were developed for each species, and were used to interpolate the probability that infection prevalence exceeded the 20% threshold across the country for both 1989 and 2009. Maps for each species were integrated to estimate combined STH prevalence using the law of total probability and incorporating a correction factor to adjust for associations between species. Population census data were combined with risk models and projected to estimate the population at risk and requiring treatment in 2009. In most areas for 2009, there was high certainty that endemicity was below the 20% threshold, with areas of endemicity ≥ 20% located around the shores of Lake Victoria and on the coast. Comparison of the predicted distributions for 1989 and 2009 show how observed STH prevalence has gradually decreased over time. The model estimated that a total of 2.8 million school-age children live in districts which warrant mass treatment. CONCLUSIONS Bayesian space-time geostatistical models can be used to reliably estimate the combined observed prevalence of STH and suggest that a quarter of Kenya's school-aged children live in areas of high prevalence and warrant mass treatment. As control is successful in reducing infection levels, updated models can be used to refine decision making in helminth control.
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Affiliation(s)
- Rachel L Pullan
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
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Sturrock HJW, Gething PW, Clements ACA, Brooker S. Optimal survey designs for targeting chemotherapy against soil-transmitted helminths: effect of spatial heterogeneity and cost-efficiency of sampling. Am J Trop Med Hyg 2010; 82:1079-87. [PMID: 20519603 DOI: 10.4269/ajtmh.2010.09-0702] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Implementation of helminth control programs requires information on the distribution and prevalence of infection to target mass treatment to areas of greatest need. In the absence of data, the question of how many schools/communities should be surveyed depends on the spatial heterogeneity of infection and the cost efficiency of surveys. We used geostatistical techniques to quantify the spatial heterogeneity of soil-transmitted helminths in multiple settings in eastern Africa, and using the example of Kenya, conducted conditional simulation to explore the implications of alternative sampling strategies in identifying districts requiring mass treatment. Cost analysis is included in the simulations using data from actual field surveys and control programs. The analysis suggests that sampling four or five schools in each district provides a cost-efficient strategy in identifying districts requiring mass treatment, and that efficiency of sampling was relatively insensitive to the number of children sampled per school.
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Affiliation(s)
- Hugh J W Sturrock
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
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Sturrock HJW, Tompkins DM. Avian malaria (Plasmodium spp) in yellow-eyed penguins: investigating the cause of high seroprevalence but low observed infection. N Z Vet J 2007; 55:158-60. [PMID: 17676079 DOI: 10.1080/00480169.2007.36761] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [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: 10/18/2022]
Abstract
AIM To investigate the cause of a high seroprevalence of antibodies to Plasmodium spp known to cause avian malaria, but extremely low levels of observed infection, in yellow-eyed penguins, Megadyptes antipodes. METHODS A polymerase chain reaction (PCR) test specific for malarial parasites was applied to DNA extracted from blood samples collected from 143 yellow-eyed penguins from an area where seroprevalence for malarial antibodies was known to be high but no parasites were observed in blood smears. RESULTS None of the samples tested positive for malarial parasite DNA using the PCR test. Assuming a sensitivity of 90% for this test, this means that prevalence of infection was 95% likely to be <2.3% in this population during this sampling period. CONCLUSIONS Serological studies of a population of adult yellow-eyed penguins indicated a high level of exposure to avian malaria parasites, but a correspondingly high level of infection was not observed and no evidence of malarial parasite DNA was found in the current study. Discrepancies between these findings and historical records of Plasmodium spp found in blood smears and post mortem may be explained either by inaccuracy of the serological test used, or by infection occurring in juveniles which is subsequently cleared in surviving adults.
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Affiliation(s)
- H J W Sturrock
- Department of Zoology, University of Otago, Dunedin, New Zealand
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