Janet T Midega
Overview
Explore the profile of Janet T Midega including associated specialties, affiliations and a list of published articles.
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13
Citations
460
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Recent Articles
1.
Muloi D, Jauneikaite E, Anjum M, Essack S, Singleton D, Kasudi M, et al.
Lancet Microbe
. 2023 Nov;
4(12):e1056-e1062.
PMID: 37977165
The intersection of human, animal, and ecosystem health at One Health interfaces is recognised as being of key importance in the evolution and spread of antimicrobial resistance (AMR) and represents...
2.
Baker K, Jauneikaite E, Nunn J, Midega J, Atun R, Holt K, et al.
Lancet Microbe
. 2023 Nov;
4(12):e1035-e1039.
PMID: 37977164
Nearly a century after the beginning of the antibiotic era, which has been associated with unparalleled improvements in human health and reductions in mortality associated with infection, the dwindling pipeline...
3.
Wheeler N, Price V, Cunningham-Oakes E, Tsang K, Nunn J, Midega J, et al.
Lancet Microbe
. 2023 Nov;
4(12):e1063-e1070.
PMID: 37977163
Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance...
4.
Baker K, Jauneikaite E, Hopkins K, Lo S, Sanchez-Buso L, Getino M, et al.
Lancet Microbe
. 2023 Nov;
4(12):e1047-e1055.
PMID: 37977162
Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to...
5.
Jauneikaite E, Baker K, Nunn J, Midega J, Hsu L, Singh S, et al.
Lancet Microbe
. 2023 Nov;
4(12):e1040-e1046.
PMID: 37977161
Integration of genomic technologies into routine antimicrobial resistance (AMR) surveillance in health-care facilities has the potential to generate rapid, actionable information for patient management and inform infection prevention and control...
6.
Guerra C, Reiner Jr R, Perkins T, Lindsay S, Midega J, Brady O, et al.
Parasit Vectors
. 2014 Jun;
7:276.
PMID: 24946878
Background: Pathogen transmission by mosquitos is known to be highly sensitive to mosquito bionomic parameters. Mosquito mark-release-recapture (MMRR) experiments are a standard method for estimating such parameters including dispersal, population...
7.
Walker M, Winskill P, Basanez M, Mwangangi J, Mbogo C, Beier J, et al.
Parasit Vectors
. 2013 Dec;
6:311.
PMID: 24330615
Background: The distribution of anopheline mosquitoes is determined by temporally dynamic environmental and human-associated variables, operating over a range of spatial scales. Macro-spatial short-term trends are driven predominantly by prior...
8.
Mwangangi J, Muturi E, Muriu S, Nzovu J, Midega J, Mbogo C
Parasit Vectors
. 2013 Apr;
6:114.
PMID: 23601146
Background: The scaling up of malaria vector control efforts in Africa has resulted in changing the malaria vectorial systems across different ecological settings. In view of the ongoing trends in...
9.
Mwangangi J, Mbogo C, Orindi B, Muturi E, Midega J, Nzovu J, et al.
Malar J
. 2013 Jan;
12:13.
PMID: 23297732
Background: Over the past 20 years, numerous studies have investigated the ecology and behaviour of malaria vectors and Plasmodium falciparum malaria transmission on the coast of Kenya. Substantial progress has...
10.
Midega J, Smith D, Olotu A, Mwangangi J, Nzovu J, Wambua J, et al.
Nat Commun
. 2012 Feb;
3:674.
PMID: 22334077
Studies of the fine-scale spatial epidemiology of malaria consistently identify malaria hotspots, comprising clusters of homesteads at high transmission intensity. These hotspots sustain transmission, and may be targeted by malaria-control...