tetano
Editor, Senior Moderator
Philos Trans R Soc Lond B Biol Sci. 2019 Sep 30;374(1782):20190020. doi: 10.1098/rstb.2019.0020. Epub 2019 Aug 12.
[h=1]Mobile phone-based surveillance for animal disease in rural communities: implications for detection of zoonoses spillover.[/h] Thumbi SM[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Njenga MK[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Otiang E[SUP]2[/SUP], Otieno L[SUP]2[/SUP], Munyua P[SUP]4[/SUP], Eichler S[SUP]1[/SUP], Widdowson MA[SUP]4,[/SUP][SUP]5[/SUP], McElwain TF[SUP]1[/SUP], Palmer GH[SUP]1,[/SUP][SUP]3[/SUP].
[h=3]Author information[/h] 1 Paul G Allen School for Global Animal Health, Washington State University, Pullman, WA 99164-7090, USA. 2 Center for Global Health Research, Kenya Medical Research Institute, PO Box 1578-4100, Kisumu, Kenya. 3 Washington State University-Global Health Program, Washington State University, PO Box 72938-00200, Nairobi, Kenya. 4 Division of Global Health Protection, Center for Global Health, Centers for Disease Control and Prevention, PO Box 606-00621, Nairobi, Kenya. 5 Division of Global Health Protection, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
[h=3]Abstract[/h] Improving the speed of outbreak detection and reporting at the community level are critical in managing the threat of emerging infectious diseases, many of which are zoonotic. The widespread use of mobile phones, including in rural areas, constitutes a potentially effective tool for real-time surveillance of infectious diseases. Using longitudinal data from a disease surveillance system implemented in 1500 households in rural Kenya, we test the effectiveness of mobile phone animal syndromic surveillance by comparing it with routine household animal health surveys, determine the individual and household correlates of its use and examine the broader implications for surveillance of zoonotic diseases. A total of 20 340 animal and death events were reported from the community through the two surveillance systems, half of which were confirmed as valid disease events. The probability of an event being valid was 2.1 times greater for the phone-based system, compared with the household visits. Illness events were 15 times (95% CI 12.8, 17.1) more likely to be reported through the phone system compared to routine household visits, but not death events (OR 0.1 (95% CI 0.09, 0.11)). Disease syndromes with severe presentations were more likely to be reported through the phone system. While controlling for herd and flock sizes owned, phone ownership was not a determinant of using the phone-based surveillance system, but the lack of a formal education, and having additional sources of income besides farming were associated with decreased likelihood of reporting through the phone system. Our study suggests that a phone-based surveillance system will be effective at detecting outbreaks of diseases such as Rift Valley fever that present with severe clinical signs in animal populations, but in the absence of additional reporting incentives, it may miss early outbreaks of diseases such as avian influenza that present primarily with mortality. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
[h=4]KEYWORDS:[/h] One Health; community-based surveillance; emerging infections; zoonoses
PMID: 31401960 DOI: 10.1098/rstb.2019.0020
[h=1]Mobile phone-based surveillance for animal disease in rural communities: implications for detection of zoonoses spillover.[/h] Thumbi SM[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Njenga MK[SUP]1,[/SUP][SUP]2,[/SUP][SUP]3[/SUP], Otiang E[SUP]2[/SUP], Otieno L[SUP]2[/SUP], Munyua P[SUP]4[/SUP], Eichler S[SUP]1[/SUP], Widdowson MA[SUP]4,[/SUP][SUP]5[/SUP], McElwain TF[SUP]1[/SUP], Palmer GH[SUP]1,[/SUP][SUP]3[/SUP].
[h=3]Author information[/h] 1 Paul G Allen School for Global Animal Health, Washington State University, Pullman, WA 99164-7090, USA. 2 Center for Global Health Research, Kenya Medical Research Institute, PO Box 1578-4100, Kisumu, Kenya. 3 Washington State University-Global Health Program, Washington State University, PO Box 72938-00200, Nairobi, Kenya. 4 Division of Global Health Protection, Center for Global Health, Centers for Disease Control and Prevention, PO Box 606-00621, Nairobi, Kenya. 5 Division of Global Health Protection, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.
[h=3]Abstract[/h] Improving the speed of outbreak detection and reporting at the community level are critical in managing the threat of emerging infectious diseases, many of which are zoonotic. The widespread use of mobile phones, including in rural areas, constitutes a potentially effective tool for real-time surveillance of infectious diseases. Using longitudinal data from a disease surveillance system implemented in 1500 households in rural Kenya, we test the effectiveness of mobile phone animal syndromic surveillance by comparing it with routine household animal health surveys, determine the individual and household correlates of its use and examine the broader implications for surveillance of zoonotic diseases. A total of 20 340 animal and death events were reported from the community through the two surveillance systems, half of which were confirmed as valid disease events. The probability of an event being valid was 2.1 times greater for the phone-based system, compared with the household visits. Illness events were 15 times (95% CI 12.8, 17.1) more likely to be reported through the phone system compared to routine household visits, but not death events (OR 0.1 (95% CI 0.09, 0.11)). Disease syndromes with severe presentations were more likely to be reported through the phone system. While controlling for herd and flock sizes owned, phone ownership was not a determinant of using the phone-based surveillance system, but the lack of a formal education, and having additional sources of income besides farming were associated with decreased likelihood of reporting through the phone system. Our study suggests that a phone-based surveillance system will be effective at detecting outbreaks of diseases such as Rift Valley fever that present with severe clinical signs in animal populations, but in the absence of additional reporting incentives, it may miss early outbreaks of diseases such as avian influenza that present primarily with mortality. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
[h=4]KEYWORDS:[/h] One Health; community-based surveillance; emerging infections; zoonoses
PMID: 31401960 DOI: 10.1098/rstb.2019.0020