Top

Published in:

Open Access 01-12-2018 | Commentary

Innovation to impact in spatial epidemiology

Author: Andrew J. Tatem

Published in: BMC Medicine | Issue 1/2018

Abstract

Spatial epidemiology is a rapidly advancing field, pushing our abilities to measure, monitor and map pathogens at increasingly finer spatiotemporal scales. However, these scales often do not align with the abilities of control programmes to act at them, building a disconnect between academia and implementation. Efforts are being made to feed innovations into government, build spatial data skills, and strengthen links between disease control programmes and universities, yet work remains to be done if goals for disease control, elimination and ‘leaving no one behind’ are to be met.

Kirby RS, Delmelle E, Eberth JM. Advances in spatial epidemiology and geographic information systems. Ann Epidemiol. 2017;27(1):1–9.CrossRef

Dowell SF, Blazes D, Desmond-Hellman S. Four steps to precision public health. Nature. 2016;540(7632). https://www.nature.com/news/four-steps-to-precision-public-health-1.21089. Accessed 23 Oct 2018.CrossRef

Salje H, Lessler J, Endy TP, Curriero FC, Gibbons RV, Nisalak A, Nimmannitya S, Kalayanarooj S, Jarman RG, Thomas SJ, et al. Revealing the microscale spatial signature of dengue transmission and immunity in an urban population. Proc Natl Acad Sci U S A. 2012;109(24):9535–8.CrossRef

Hay SI, George DB, Moyes CL, Brownstein JS. Big data opportunities for global infectious disease surveillance. PLoS Med. 2013;10(4):e1001413.CrossRef

Kangoye DT, Noor A, Midega J, Mwongeli J, Mkabili D, Mogeni P, Kerubo C, Akoo P, Mwangangi J, Drakeley C, et al. Malaria hotspots defined by clinical malaria, asymptomatic carriage, PCR and vector numbers in a low transmission area on the Kenyan Coast. Malar J. 2016;15:213.CrossRef

Seyoum D, Yewhalaw D, Duchateau L, Brandt P, Rosas-Aguirre A, Speybroeck N. Household level spatio-temporal analysis of Plasmodium falciparum and Plasmodium vivax malaria in Ethiopia. Parasit Vectors. 2017;10(1):196.CrossRef

Kreuels B, Kobbe R, Adjei S, Kreuzberg C, von Reden C, Bater K, Klug S, Busch W, Adjei O, May J. Spatial variation of malaria incidence in young children from a geographically homogeneous area with high endemicity. J Infect Dis 2008;197(1):85–93.CrossRef

Bousema T, Griffin JT, Sauerwein RW, Smith DL, Churcher TS, Takken W, Ghani A, Drakeley C, Gosling R. Hitting hotspots: spatial targeting of malaria for control and elimination. PLoS Med. 2012;9(1):e1001165.CrossRef

Takahashi S, Metcalf CJE, Ferrari MJ, Tatem AJ, Lessler J. The geography of measles vaccination in the African Great Lakes region. Nat Commun. 2017;8:15585.CrossRef

10.

Buckee CO, Cardenas MIE, Corpuz J, Ghosh A, Haque F, Karim J, Mahmud AS, Maude RJ, Mensah K, Motaze NV, et al. Productive disruption: opportunities and challenges for innovation in infectious disease surveillance. BMJ Glob Health. 2018;3(1):e000538.CrossRef

11.

Omumbo JA, Noor AM, Fall IS, Snow RW. How well are malaria maps used to design and finance malaria control in Africa? PLoS One. 2013;8(1):e53198.CrossRef

12.

Brown DW, Burton AH, Feeney G, Gacic-Dobo M. Avoiding the will o’ the wisp: challenges in measuring high levels of immunization coverage with precision. World J Vaccin. 2014;4(3):97–9.CrossRef

13.

Cutts FT, Claquin P, Danovaro-Holliday MC, Rhoda DA. Monitoring vaccination coverage: defining the role of surveys. Vaccine. 2016;34(35):4103–9.CrossRef

14.

Thomson DR, Stevens FR, Ruktanonchai NW, Tatem AJ, Castro MC. GridSample: an R package to generate household survey primary sampling units (PSUs) from gridded population data. Int J Health Geogr. 2017;16(1):25.CrossRef

15.

Delmelle EM, Zhu HM, Tang WW, Casas I. A web-based geospatial toolkit for the monitoring of dengue fever. Appl Geogr. 2014;52:144–52.CrossRef

16.

Clinton Health Access Initiative. Using Satellite and Cell Phone Data to Eliminate Malaria in Namibia. Data Impact Case Studies; 2015. https://dataimpacts.org/wp-content/uploads/2015/06/phone-records-track-malaria.compressed.pdf. Accessed 23 Oct 2018.

17.

Wardrop NA, Jochem WC, Bird TJ, Chamberlain HR, Clarke D, Kerr D, Bengtsson L, Juran S, Seaman V, Tatem AJ. Spatially disaggregated population estimates in the absence of national population and housing census data. Proc Natl Acad Sci U S A. 2018;115(14):3529–37.CrossRef

Title: Innovation to impact in spatial epidemiology
Author: Andrew J. Tatem
Publication date: 01-12-2018
Publisher: BioMed Central
Published in: BMC Medicine / Issue 1/2018
Electronic ISSN: 1741-7015
DOI: https://doi.org/10.1186/s12916-018-1205-5

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Innovation to impact in spatial epidemiology

Abstract

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 1/2018

Melatonin and health: an umbrella review of health outcomes and biological mechanisms of action

Deprescribing preventive cardiovascular medication in patients with predicted low cardiovascular disease risk in general practice – the ECSTATIC study: a cluster randomised non-inferiority trial

Recently resettled refugee women-at-risk in Australia evidence high levels of psychiatric symptoms: individual, trauma and post-migration factors predict outcomes

Healthcare costs and utilization associated with high-risk prescription opioid use: a retrospective cohort study

Addressing ethnic inequalities in the pathways to care for psychosis

Chronic morbidity, deprivation and primary medical care spending in England in 2015-16: a cross-sectional spatial analysis