Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology

ISSN No:-2456-2165

Use of Interactive 3-Module Integrated Livestock

Health Service Mobile Application-Livestock Diseases
Adaptive Capacity and Capability Building
Ngari P. Muriuki1*, David N. Ndung’u2, Stephen Ongalo3, Rosemary N. Ngotho-Esilaba2
1. Kenya Agricultural and Livestock Research Organization (KALRO), Biotechnology Research Institute (BioRI)-Muguga, P.O. Box
362-009002, Kikuyu, Kenya.
2. Kenya Agricultural and Livestock Research Organization (KALRO), Veterinary Science Research Institute (VSRI)-Muguga, P.O
Box 32-00902, Kikuyu, Kenya.
3. Department of Electrical and Information Engineering, University of Nairobi, P. O. Box 30197 - 00100. Nairobi, Kenya.
*Correspondence;
†
Equally contributing Author

Abstract:- Integrated veterinary service mobile I. INTRODUCTION

applications provides a faster, nearly real-time, and
accurate reporting of livestock diseases. Active In the past, disease incidence reporting relied on pen and
participatory epidemiological data collection using an paper for reporting and data collection. Technological
online platform forms a prerequisite for early detection advancements have allowed not only digitization of data
and response which prevents the spread of the disease collection but also real-time data transfer. Digitizing this
outside the foci of the outbreak. Compared to the process has hastened the response by enabling mobilization of
traditional pen and paper method, the use of mobile all involved stakeholders with a touch of a button and in a
applications was faster and reliable and connected farmers real-time manner. Digital processing and storage of disease
to animal healthcare service providers more reliably. In data form a disease reporting database from which geo-health
the backend, the disease data was aggregated by animal analytics and dynamics of various diseases can be made
species and to farmer biodata and geolocation. Animal possible. In the same light, the technological surveillance tools
health care provider module allowed a quick response developed will enhance almost real-time reporting of disease
focusing on spatial location. Detailed list of signs and incidence in Arid and Semi-Arid Lands (ASAL), upgrading
symptoms as described by the farmer allowed a putative the rigorous and time-consuming method. Chethan Kumar et
disease diagnosis and follow-up at all administrative levels. al., 2021) Pilot studies have shown that this model can be very
Researchers, we are able to collect current epidemiological sustainable as a three-face business model connecting the
data of the most prevalent diseases of cattle, sheep, and main actors in the community benefiting across professional,
goats. Most of the diseases reported through the app were social, and economic spectra.
classified as notifiable diseases in Kenya which impose
international livestock trade restrictions. Initially, heavy Kenya in the past years has had an increase in livestock
losses are occasioned in livestock due to lack of reliable population going by the statistics over the years since 2009,
reporting to facilitate faster response. The tool was also and the recent in 2019, that is, 2.3 million animals by Kenya
able to map and assess the disease burden and potential National Bureau of Statistics (Livestock Population - Kenya
zoonotic disease risk. Although reporting through the e- National Bureau of Statistics, 2019.). Prediction of trends in
platform resulted in much more timely and reliable the future can be based on the valid available data in that an
reporting and feedback, limited connectivity and lack of increase is expected as well as determining the expectancy of
smartphones in some regions delayed the process. produce increase of animal food sources (Merianos, 2007).
However, in the long run, with the widespread use of Arid and semi-Arid regions account for over 60% in the past
smartphones, the approach will greatly improve animal years. A background check on its marginalization then the
disease reporting and surveillance, enhance data integrity, various challenges that the ASAL’s areas experience in terms
and enhance disease response strategies. Field data of livestock keeping varies from the technological aspect of
collection, transmission, and analysis allowed veterinary services provision, elaboration of reporting, and
dissemination of validated feedback prompting an collection of data. Therefore, Information Communication
immediate response, and served as an early warning Technology (ICT) is a big player in the new age information
response. system in the light of one health approach, enhancing
detection, almost real-time reporting and response, then there
is a need to have a surveillance tool that that incorporates

IJISRT23MAY1822 www.ijisrt.com 3254

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
technology in service delivery (Karimuribo et al., 2017).This surfacing. Two methods were applied; quantitative study of
research details a technology surveillance tool used by farmers epidemiological alerts, followed by an in-depth qualitative
to record data and the developers in processing it. The data collection by interviews using the methods described by
technology was aimed at having a variety of information; to determine the completeness of data.
disease incidence, treatment practices, antibiotics, vaccines,
and animal health services reliability in conjunction with II. MATERIAL AND METHODS
affordability. However, not only can the technology be used in
assessment of the above, but also other animals, human  Study Area
disease surveillance, and even other agricultural purposes. The The study was conducted in Kajiado County of Kenya
application examined data collection, analysis, presentation, located within the Rift Valley region of Kenya spanning an
and reporting findings on disease surveillance. The core area of 21,292 sq kilometers. It borders Nairobi, Kiambu,
objective of the research was to establish a disease Machakos Taita Taveta and Norok counties bordering
surveillance database and collect data represented on a Tanzania to its South. It has an estimated population of
recurrent geographical map which is important in the 117,840. Agro-pastoralism and nomadic pastoralism are the
provision of data regularly on animal health status and give main livestock production systems practiced and participants
variation in seasonality. were selected based on these criteria. The study was a
collaborative project between Veterinary science Research
Many disease reporting e-platforms have been developed Institute (VSRI)- Muguga of Kenya Agricultural & Livestock
(Animal Disease Information System (ADIS), Research Organization (KALRO), University of Nairobi
2020)(Hernández-Jover et al., 2021). A similar approach was (UON), Directorate of Veterinary Services (DVS) Kajiado and
made for epidemiological risk surveillance (Lesmanawati et Ministry of Interior and Coordination through area and local
al., 2020), ranks diseases risks by relevance to country and authorities. This research was funded by Kenya Climate Smart
epidemiological risk as per periodical epidemics. This was Agricultural Program (KCSAP). Selected locations of the
devolved further in our approach to report and capture data study included; Magadi, Matapato South, Rombo, Matapato
from the village level. The surveillance technology app was North, Kenyawapoka, Dalaketuk, Ewasokedong, Kimana and
objectively used in the prediction of future health risks, using Imaroro locations.
information on animal disease dynamics with climate change
and human factors. This is to enhance change and adaptive  Study Design
behavior in nomadic pastoral communities. In addition, Descriptive study was based on the analysis of routine
assessment of emerging and reemerging diseases that have the data transmitted by Community Disease Reporters (CDRs)
potential to be epidemic and have socio- economic impact on from all selected areas. A total of 109 community disease
farmers in terms of mortality and morbidity (Wu et al., 2016). reporters (CDRs) were identified with the help of Kajiado
For example, during an outbreak of animal disease, County Directorate of Veterinary service (CDVS) and the
intervention can be done by restricting animal movement to local chiefs. The CDRs were trained on the use of technology
slow down and stop the transmission of diseases to other as a reporting tool for diseases. The phone application was
regions. installed in their phones and subsequently trained on data
entry. Participants were selected based on the criteria that
This tool will be of importance to various stakeholders’ they had a heterogenous herd composed of cattle, sheep, and
locally, regionally, and globally. It seeks to benefit the goats. The study involved participants from 11 regions, from
government by ensuring that resource mobilization for each region, 10 representatives were picked to represent the
sustainable health management is appropriately distributed, for village or a location. Questionnaires were also administered to
instance; in case of an outbreak of a disease in a certain area, 102 participants in nine focus group discussions at selected
then vaccines or drugs can be distributed to them to solve the sites to assess the completeness of data.
situation instead of mis appropriately distributed equally even
to areas that are not endemic. The researchers also become  Mobile Application Architecture & tools
beneficiaries through understanding on the disease trends in The architecture of the app was split into three main
predicting the future and know on which research topics to layers, namely; user layer, network abstraction layer, and
pick on, also farmers get to benefit from health care through cloud infrastructure. User layer includes the user interfaces
direct linkage to the Animal Health Assistant and Veterinary utilized in data collection and visualization. It also features the
Officers in treatment and managing diseases The disease basic app functionality such as user location determination,
surveillance database was developed using new open-source camera protocols, etc. Network abstraction layer is the internet
technology that are easily retrievable (Guernier et al., 2016; connectivity of the user devices that allows data to be posted
McGreevy et al., 2017) Building on such previous studies, we to the cloud database as well as uploading of the picture files
used new language technologies to improve real-time data associated with each post. Cloud infrastructure has three main
information generation and retrieval. Real-time information components. The online database that holds all user data, the
generation is an uphill endeavor from previous technologies. authentication layer for security, and cloud storage to store the
This involves a geolocated skeleton mapping of data picture files sent by users.

IJISRT23MAY1822 www.ijisrt.com 3255

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
The architecture can be summarized as follows:  Data Analysis
Data was extracted from the backend interface of the
surveillance platform, manually organized in Microsoft Excel,
and cleaned. It was then classified into key thematic areas of
the surveillance platform to allow qualitative analysis. It was
then exported to GraphPad Prism version 9.3 and analyzed,
then presented using charts, graphs, and spatial representation
on climate maps for temperature and rainfall. Collectively,
qualitative data were synthesized and identified the capacity
and capability of an integrated veterinary service mobile
application alongside its constraints. A thematic illustration of
the various diseases focusing on space was created to
summarize the key findings.

III. RESULTS

Active farmer participation through farmers’ group

discussion established that shortage of pasture due to
The app was developed utilizing a number of open- prolonged drought and lack of water for their animals was the
source tools and platforms, namely; Android platform, main challenge in nomadic pastoralism. Diseases were the
Firebase, and Node package Manger. Android platform was second most devastating challenge due to lack of animal
utilized to create the user interface and app functionality for health products and services such as agrovet supplies,
the farmer and AHW modules. This was done using the vaccines, and veterinary services. Lack of agricultural
Android Studio IDE where elements of the user interface were extension services ranked third due to the few numbers of
designed using the XML language while the functionality was extension officers covering a very wide area. Wildlife conflict
developed using the Kotlin language. Firebase, which is a ranked the least challenge in the ASAL area of Kajiado.
Backend-as-a-service (BaaS) app development platform, was Wildlife conflicts may arise within human-livestock-wildlife
utilized to host the app as well as give cloud functionality to interfaces when farmers raid parks for pasture and when
the app. Through this, an online database was setup to allow wildlife raid agropastoral areas. These interactions were
for the gathering of data from the app. It also allows for the observed to increase the risk of disease.
setup of security features, i.e., user authentication, as well as
cloud storage for photos taken through the app. All this was
done using the Firebase Fire-store tool for the online database,
Firebase Authentication tool for security features, and
Firebase Storage tool for cloud storage. Node Package
Manager (NPM) was utilized for the development of the
server functions through the use of the TypeScript language.

As part of a capacity and capability building initiative,

the app was disseminated through direct installation of the app
APK into the phones of selected farmers and animal
healthcare providers. The farmers were then taken through the
prompts of the system, recording their biodata as well as the
reporting of animal cases and underlying syndromes and
medical interventions made by them, further allowing the
animal health professional to have a wholistic view of the
reported case. This was further enhanced by the farmer being
required to submit a photo of the sick/dead animals. The same
mobile application was provided to selected animal health
workers of the region. They were also taken through the Fig 1: Proportional challenges reported to affect livestock
reporting process that the farmers went through as well as the farmers in Kajiado County
case solving process through the application. From the back
end hosting the research and admin module, data was
organized, processed, and synthesized.

IJISRT23MAY1822 www.ijisrt.com 3256

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165

 Animal Disease Reporting

Fig 3: Proportional cattle disease incidence reported over the

study period

 Sheep and Goats’ Diseases

Diseases that were reported in many cases in Kajiado
county were; Sheep and Goat pox, PPR, bluetongue virus,
anthrax, CCPP, enterotoxaemia, pink eye, heartwater,
Fig 2: Map of Kajiado, Kenya, showing relative disease hemonchosis and mange. Small ruminants are more
burden reported susceptible to diseases than large ruminants. As such, viral
diseases showed the highest prevalence in small ruminants,
 Cattle Diseases 43% (per cent), with PPR showing the highest prevalence of
In cattle, the viral diseases that were frequently reported all cases reported. Heartwater has been an emerging disease
include lumpy skin, FMD, bluetongue virus, and pox. with a relatively high prevalence rate. The farmers described
Bacterial diseases include pink eye and foot rot. Protozoan the diseases by their clinical symptoms, for instance, PPR was
diseases include trypanosomiasis, ECF, and mange. described by dysentery, nasal discharge, and lesions in the
Helminthiasis includes the bottle jaw. Cattle showed a high mouth. Heartwater was described by their clinical symptoms
prevalence of lumpy skin disease in the region, and per of imbalance and confusion. CCPP was described as nasal
location trypanosomiasis was more prevalent in Magadi. discharge, respiratory distress, lack of appetite and coughing,
Magadi location had the highest cumulative reporting for all and sudden death. Magadi locations had the largest
diseases categorized. Cattle are the most important livestock to representation of cumulative totals of disease occurrence when
the Maasai community. Being a small community, set back by ranked per location. Hemonchosis coenurosis was the most
new information and technology, Maasai people struggle to prevalent helminthiasis of all diseases reported in small stocks.
treat their cattle or find professional assistance. Pink eye was Hemonchosis was characterized majorly by anaemia, bottle
the least reported of all cattle diseases found in the study area. jaw, and diarrhea. Coenurosis was characterized by confusion
When ranked by occurrence; lumpy skin disease, and loss of balance in the animals. Moreover, spinal cyst was
trypanosomiasis, and FMD were the diseases of most concern common among the small stock where sheep and goats
in the Kajiado region. Among the classes of diseases, viral presented with paralysis.
diseases showed the most prevalence at 56%, protozoan
diseases 29%, helminthiasis 9%, and bacterial diseases at 6%.

IJISRT23MAY1822 www.ijisrt.com 3257

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
anthelminthic drug. Tetracycline and PenStrep (penicillin and
Streptomycin) were the most used to remedy for most
diseases, viral and bacterial. Furthermore, participants
identified that they used Novidium to treat trypanosomiasis
and Buparvaquone to treat ECF. Cases of wrong prescription
were also identified during the study whereby the Maasai
farmers revealed to use Novidium as an anthelminthic: they
dissolved the tablet in water and administered it orally.
Participants also mentioned that they applied tradional
methods in some cases, for instance, washing with
concentrated salt solution and acaricides, to treat LSD in
cattle, goats, and sheep pox. Some farmers stated that they
managed goat and sheep pox using applied directly to the
lesion on the animals. Magadi salt to treat and prevent foot rot
was applied as a solution in muddy animal sheds during the
rainy season. Levamisole, Ivermectin, and benzimidazole
(albendazole) are anthelmintic drugs used for the control of
helminths and parasites. Levamisole accounted for the most
widely used anthelmintic drug in our area of study.
Fig 4: Proportional shots diseases reported in Kajiado county
Antimicrobials used include tetracyclines, macrolides, beta-
over the study period.
lactam aminoglycosides, diminizines, levocetirizine,
quinolones and novidium. Antimicrobials commonly used in
 Animal Treatment and Care. Kajiado County were categorized and summarized below.
Animal health treatment and care services were low in
Kajiado county (19.27%). In fact, this has led the majority of
the treatments to come from the farmers themselves (58.85%).
Veterinary services are required as locals may injure or
misdiagnose the animal during treatment and care. In some
areas, the animal health assistants and farmers would both
treat the animals.

Fig 6: Commonly used drugs and their classification.

 Animal disease Vaccinations

Participants felt that government intervention in
Fig 5: Proportional service delivery and commonly applied preventing disease through vaccination was quite poor,
drugs for animal treatment without equity in deployment, especially in remote areas of
Kajiado. Larger populated agropastoral regions showed higher
 Antimicrobials And Anthelmintics Used by Farmers. rates of individual vaccination initiatives. Cattle were
Majority of participants indicated that they treated their vaccinated at a lower rate compared to small ruminants. The
animals individually due to the unavailability of veterinarian median vaccination value was average on an empirical
services, and if present, they were unreliable. Antibiotics that presentation but stable, considering the region regarding
were commonly used in Kajiado county were; penicillin- socio-economic status of the most impoverished farmers. As
streptomycin, tylosin, oxytetracycline, Meriquin, and shown per the data, small ruminants were given more attention
ivermectin. Tetracycline was the most used broad-spectrum compared to cattle, with some associated factors being the
antibiotic to treat most diseases, some participants stated that ease of managing the small ruminants, culture of trade, and
they used tetracycline concentrations from 5 to 30%. Most community-based economics, which indicate the animals to be
participants used ivermectin as both an antibiotic and quite economical.

IJISRT23MAY1822 www.ijisrt.com 3258

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
surveillance using a participatory framework. This approach
achieves its functionality through its three key inputs: Real
time reporting of diseases by farmers at the grassroots level,
updating on the risk presenting and the measures to take from
the backend interface; intervention of the reported cases
through linking farmers to preregistered animal health care
providers through the application; gathering insights from the
collected data thus allowing for a relatively more accurate
disease proliferation mapping. Regulators and key actors in
animal health can rank the disease in terms of the cases
reported and asses its economic impact. Surveillance data over
time provide surfacing data and a skeleton map which help in
enhancing capabilities against various diseases. Regular data
on the health status of the animals at the grass root equip
Fig 7: Relative livestock disease vaccination data from people with real-time data and information which interface
individual and government initiatives. direct action and precautions to take. Predictive mathematical
modelling can be utilised to analyse the future health risk.
 Animal Health Services Availability and Reliability. Through the e-platform, farmers adaptive behaviour and
Overall, veterinarian services were poor in Kajiado spread of disease can be explored to enhance the sensitivity to
County considering the livestock population and relative climate change impacts and adaptive capacity in ASAL areas.
animal treatment by farmers and the few animal healthcare
providers. Magadi region had the largest population of The application consists of three main modules: Farmer’s
participants, however, from the collected data, the veterinarian module, a platform through which the farmer is able to report
services availability was among the lowest (34.48%) and sick/dead animals as well as the associated observable
reliability even lower (3.45%). syndromes. This is also accompanied by a photo and geotag of
the location of the respective farmer to allow for a better
15 Available understanding of the situation of the farmer; Animal
Unavailable healthcare provider module: This is a platform through which
Reliable preregistered animal health care providers can solve cases and
10 further allow the accurate scientific representation of what was
Unreliable initially reported. Research and administrative modules: This
are the platform through which all data collected can be
5 manipulated, allowing for the gathering of insights as well as
mapping of diseases. It also reserves all rights of operation
within the farmer and healthcare provider modules.
0
The development process followed the agile- Rapid
le
le

le

le

Application Development (RAD) model. It is split into three

ab
b

ab

ab
ila

eli
il

li

main modules; Farmer module, Animal healthcare provider

a

va

Re

r
Av

Un
a
Un

module, and the Research and administrative module. The

Fig 8: Animal health cares availability and reliability in Farmer module entails the development of interfaces that
Kajiado county allow farmers to report cases of sick and/or dead animals from
the grassroots. It interrogates the farmer on the intervention
IV. DISCUSION previously applied. This module further allowed for the
provision of access to veterinary services through the Animal
Integrated livestock monitoring mobile application was healthcare provision module. The Animal healthcare provider
developed for data collection. The app is an Android based module entailed the development of a platform that allowed
mobile application that allows for monitoring of diseases in preregistered animal health professionals to access data on
livestock at the grassroots level. It leverages the use of mobile reported cases from the farmers module, from which these
technology to allow farmers to report cases of various diseases professionals would then provide their advice to the affected
within their stock, while at the same time getting the necessary farmers. This module provides the farmers details including
medical attention for their affected livestock. Each reported telephone numbers and geolocation for fast response. It also
case is geotagged allowing for appropriate mapping of the offers a case definition window which the animal healthcare
particular disease in the region allowing for better planning for provider updates the case definition and intervention details to
vaccination drives, a process that was initially carried out with the next module. The third phase was the development of the
an unreliable traditional pen and paper method. The main Research and administrative module. It entailed the
objective of the app is to allow for grassroots livestock disease development of a platform from which all data can be viewed,

IJISRT23MAY1822 www.ijisrt.com 3259

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
manipulated, and insights drawn from the same. Researchers unregulated use poses a great challenge to antimicrobial
would be able to access the data collected through the app, resistance. Enforcement of policies that regulate drug use is
allowing them to draw insights on the same. Simple analytics, important at the verge of AMR superbugs as we may lack
such as the proliferation of a particular disease in the region, substitutes for resistance emergencies (Florio et al., 2020).
were also a feature of the module. Misuse of certain antimicrobials may lead to AMR
development and therefore there is a need to regulate, support,
An integrated livestock health and reporting app was and monitor the use of certain important antimicrobials under
developed to facilitate faster reporting and allow better a routine pastoral setting. Injudicious use of critical
coordination of animal health systems. A pilot study involved antimicrobials presents a relatively high risk of selection for
a small-scale study conducted in Kajiado County to evaluate antimicrobial resistance, posing a threat to public health
the feasibility, capability, and capacity of mobile application threats, for example, augmenting AMR in human medicine.
in early detection of animal disease outbreaks in remote areas
by engaging community disease reporters (CDRs). Active Integrated livestock surveillance app reporting
surveillance for livestock diseases is the cornerstone of contributed significantly to reduction mortality and morbidity
decision making and practice in response and control by enhancing near real-time surveillance and response.
(Rosenberg, 2015). Improving the existing reporting systems Formers could easily report diseases and get connected to the
through the use of technology improved disease reporting with nearest animal healthcare provider for professional veterinary
near real-time response and control. Use of technology avails services. Many households in Kajiado county depend on
itself to advance the development of an integrated reporting livestock for livelihood. Empowering these farmers, the
system using data and information systems to communicate majority of whom are smallholder farmers with a reliable
efficiently and effectively at all levels of disease control. reporting and feedback platform not only enhance security for
Automation of capture and data analysis make the data readily their animals but also improve the quality of life. This study
available electronically with spatiotemporal space(Jaya & established livestock diseases and lack of veterinary services
Folmer, 2022). Engaging and empowering farmers at grassroot as the main threat to the economy of the poor marginalized
level in disease surveillance in a apastoral area improved farmers. Livestock diseases can cause a loss translating to
quick detection of disease outbreaks and response at ward, billions of dollars each year. An integrated surveillance
subcounty, county and at national level. Integrating human approach will have a positive impact in mitigating livestock
and animal health would further improve the response to diseases and enhancing farmers adaptive capabilities to these
animal and human diseases, including the zoonotic for challenges in a grassroot socio-economical and
effective one health approach (Yahya, 2021) epidemiological context. Backend analysis of epidemiological
data will enhance the mobilization and deployment of
Integrated animal health monitoring could contribute resources including enhanced vaccination programs focusing
significantly in strengthening existing AMR and anthelmintics on geographical spaces. Farmer led syndromic system of
surveillance as a precautionary measure against the risk of livestock disease surveillance presents an efficient and reliable
resistance that has a great implication on human health. and near real-time way to report surveillance data. Trained
(Mremi et al., 2022)Available data demonstrated and indicated community disease reporters (CDRs) log discernable clinical
deficiencies in the quality of the veterinary service in Kajiado presentations and upload on to the fronted end-User interface
County presented by unavailability of veterinary services and
lack of reliability. (Thumbi et al., 2019). This challenge Pastoralists have found a way to cope with the
contributed significantly to the mortality and morbidity due to uncertainties of that way of life and living in the rangelands,
the large proportion of sick animals not getting treatment, this has been seen to decline over the past recent years. They
variations in the drugs used, and inappropriate use of drugs. have been greatly influenced by climate change that has
For example, Novidium, an injectable drug, was mostly caused the death of most of their livestock due to lack of
administered orally alongside anthelmintic drugs. Most pasture and water. (Bedelian & Ogutu, 2017). Among other
farmers were observed to treat their animals and this factors, overgrazing has also greatly contributed to the
contributed to inappropriate use of drugs and irregular dosage problem of lack of pasture, as it causes the top soil to be loose,
for most diseases. Drug dosage, duration and recommended and when it rains, they are washed away. They have been able
withdrawal period were not followed by many farmers and to cope because of their extensive knowledge of their areas
this affected the outcome of the treatment of sick animals. and diseases that affect their livestock and how to control
Inadequacy and inefficiencies in veterinary care in Kajiado them. Disease risk increases with the interaction within the
County may be improved through streamlined policy and human, livestock, and wildlife interface. Diseases have the
regulation of agrovets, training of community animal health potential to affect both wildlife and livestock, especially when
workers at the grassroot level, supportive supervision, and they share the same environment. (Njenga et al., 2021)Due to
monitoring. Tetracyclines are the most commonly used drug the enormous pasture areas being converted to farms, pastoral
as we and other studies have reported (Bangura et al., 2022). mobility has decreased overtime, and their propensity for
Supervision and monitoring of these classes of drugs with sedentary lifestyles has increased. Once established, it would
strict observation of antibiotic stewardship as their wide be challenging for them to relocate in the event of sickness,

IJISRT23MAY1822 www.ijisrt.com 3260

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
whereas they would have done so in the past when there were Other factors that contribute to disease spread is: poor
vast rangelands (Ottichilo et al., 2000; Voeten & Prins, 1999). animal health services and the existing ones are no longer in
Due to their coexistence, formerly controlled diseases like use, like cattle dips which have been abandoned in many
trypanosomiasis are still a menace with diseases like ECF areas. In ASALS anima health services have deteriorated,
having devastating on livestock and having a high fatality rate. which has made it difficult for famers to access drugs and
vaccines for their livestock. Pastoralism provides livelihood to
The majority of cattle infections in the study area are 90 percent of rural families living in dryland and is one of the
believed by the pastoralist to be naturally transmitted by major economic activities for people living in arid and semi-
African buffaloes, therefore grazing livestock through the arid lands of Africa.(Bin Tarif et al., 2012)(Diuk-Wasser et
wildlife interface puts them at danger, as in the cases of East al., 2021) (Climate Change Destroys the livelihoods of Kenyan
Coast Fever (ECF) and Foot and mouth disease (FMD) Pastoralists | Africa Renewal, n.d.; Maciej Serda et al., 2013)
(Omondi et al., 2020). Animal diseases that have a high Growing human population lead to agricultural expansion and
incidence of occurrence in cattle include: ECF, increased deforestation resulting to great negative impact on
trypanosomiasis, and FMD in cattle. ECF and the environment, climate, and wildlife population. Livestock
trypanosomiasis are vector borne and they are controlled by and wildlife coexistence in areas that border wildlife zones
ectoparasite control and a combination of vaccination and increase the risk of disease in areas as wildlife are potential
acaricide spraying in the case of ECF. ECF is a disease spread natural reservoirs of livestock disease (Mworia et al., 2008).
by ticks, it has a significant impact on animal output. In Grazing livestock in wild life lands expose them to these
addition to being found on livestock, ticks are also found in diseases. When wildlife trespass onto human land, they run the
wildlife, and their interactions has made tick management less risk of being hurt because people want to stop any losses they
effective (SONENSHINE et al., 2002). Trypanosomiasis is might create due to arising human wildlife conflict.(Tyrrell et
spread by tsetse flies; some wildlife can harbor the disease al., 2017). Although wildlife-protected zones have been
without showing any clinical signs making them natural established, this cannot be totally relied upon to sustain
reservoirs. There has been reemergence of trypanosomiasis biodiversity because wildlife is a migratory species and will
due to poor management practices and decreased veterinarian eventually move into human areas. Additionally, wildlife has
services in the endemic areas (Okello et al., 2022). FMD being seasonal migration, such as in the case of the wildebeest, and
a highly contagious viral disease that affects domestic and must relocate. Due to the collapse of government veterinary
wild even-toed ungulates, has been identified to have a high services and the decreased availability of medications and
incidence in cattle. Foot and mouth high transmissibility and vaccines, previously controlled diseases have begun to
impact on livestock health and its value chain makes it the reemerge in certain regions, indicating a decline in disease
most economically important transboundary animal disease. control(Kenya - Food Security Outlook Update: Sat, 2022-12-
(Understanding the Socioeconomic Impact of Foot-and-Mouth 31 | Famine Early Warning Systems Network, 2022.). Disease
Disease Control in Kenya | The Cattle Site, 2020.). It imposes transmission can be mitigated by utilizing vector management
restrictions to local and international trade constraining on the techniques, such as bush burning in tsetse fly infected areas,
development of country pastoralism, where large herds of the use of acaricides to prevent diseases transmitted by ticks,
cattle mingle was attributed to be a contributing factor in the and vaccination to stave off future infections. The
disease's rapid spread. quarantining of domestic animals and the isolation of wildlife
reserves during crucial transmission periods can both prevent
Sheep and goats are the most kept livestock by the the spread of illnesses from wildlife to livestock.
pastoralist communities in ASLAS areas(Kenya’s Sheep and
Goat Meat Market Report 2023 - Prices, Size, Forecast, and V. CONCLUSION
Companies, 2023.). PPR, sheep and goat pox, heartwater, and
CCPP are diseases that have been identified to be the major Integrated livestock monitoring mobile application is a
problem to ``the small stock. PPR was reported to be the most real-time participatory epidemiological data collection using
common among small stocks and CCPP was more prevalent in an online platform. Early reporting enabled early response
goats. Despite the efforts made by vaccination, but because it which prevented the spread of the disease within the foci of
is less accessible to pastoralists due to poor veterinary services the outbreak and helped save the marginalized farmers
in remote pastoral areas, the disease is more common. Heart livelihoods. Through the platform, the farmers learnt how to
water has a higher incidence of occurrence in both sheep and detect diseases, report them in real-time, take the necessary
goats. The farmers have identified that the disease spread control measures through feedback, and ensure a prompt
more during the rainy season, for example, the case of response to the situation at hand. This greatly improved the
trypanosomiasis, because it spreads more in the rainy season efficiency of the field animal healthcare providers for their
and because tsetse thrive best under this climate. CCPP is also daily fieldwork, as well as the management of various diseases
a problem in cold seasons together with pneumonia in shoots. affecting the communities in the research setting. This
technology has enabled accurate and near real-time reporting
of disease, which is a key requirement in the detection of
disease outbreaks and response measures for their control. Use

IJISRT23MAY1822 www.ijisrt.com 3261

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
of mobile application tool enabled the collection of AUTHOR CONTRIBUTIONS
demographic data, geo-locations, and lists of syndromes in
addition to putative diagnosis and disease identification. Dr. Rosemary N. Ngotho-Esilaba, Stephene Ongalo and
Moreover, compared to the traditional pen and paper methods, Ngari P. Muriuki conceived the idea, coordinated this work,
the data is immediately available in real time to all mitigation developed the mobile application and trained participants how
levels via a cloud-based server. Through the E-platform, to use the app. Ngari P. Muriuki organized the data
farmers are able to report livestock diseases and get the downloaded from the cloud server, analyzed the data,
required help from the animal health providers offered through interpreted results, wrote the manuscript. David N. Njoroge
a feedback module to farmers. Researchers, we are able to and Stephen Ongalo generated the map. All the authors
collect current epidemiological data of the most prevalent approved the manuscript.
diseases of cattle, sheep, and goats. Most of the diseases
reported through the app were classified as notifiable diseases DISCLAIMER
in Kenya which impose international livestock trade The findings in this research article are those of the
restrictions. Initially, heavy losses are occasioned in livestock authors and do not necessarily represent the official position of
due to lack of reliable reporting to facilitate faster response. the donor (Kenya Climate Smart Agriculture Project
The tool is also able to map and asses the disease burden and (KCSAP)), the Ministry of Agriculture, Livestock, Fisheries
potential zoonotic disease risk. Although reporting through the State Department for Crop Development and Agricultural or
e-platform resulted in much more timely and reliable reporting those of Kenya Agricultural and Livestock Research
and feedback, limited connectivity and lack of smartphones in Organization (KALRO) nor the official position of the
some regions delayed the process. However, in the long run, Government of Republic of Kenya
with the widespread use of smartphones, the approach will
greatly improve animal disease reporting and surveillance, Data Availability
enhance data integrity, and enhance disease response All data and material that support the findings of this
strategies. Field data collection, transmission, and analysis study are included in this manuscript.
allowed dissemination of validated feedback, that prompted an
immediate response, and served as an early warning response. Funding
Central data points enabled quick analysis and validation by This study was funded by Kenya Climate Smart
veterinary epidemiologists and ensured immediate and safe Agriculture Project (KCSAP) through the Ministry of
sharing of data among health care providers, decision makers, Agriculture, Livestock, Fisheries State Department for Crop
public health officials, diagnostic labs, and wildlife service Development and Agricultural for Livestock Applied
departments. Strong surveillance and reporting capacity of the Research grant-A One Health Approach to Understanding the
mobile application contributes to enhanced early warning of Epidemiology of Emerging Zoonotic Viral Diseases in
animal disease occurrence at the grassroot level. This greatly Changing Climates.
reduced delays in feedback and response to disease outbreaks,
saving time, resources, and livelihoods with a touch of a Conflict of interest
button. Cloud based database system created offers storage of The authors have no competing interest.
real-time georeferenced animal disease reports which is easily
accessible. Ethical Statement
This work did not require neither sampling nor
ACKNOWLEDGEMENT experimentation on animals or humans. However, informed
consent was taken from animal owners during data collection.
We would like to acknowledge Kenya Climate Smart In addition, the handling of animals was overseen by the
Agriculture Project (KCSAP) for providing funding for this appropriately qualified veterinarian under the normal
research and the development of an Integrated Livestock procedures approved by the Animal care and Use committee
Disease Reporting E-Platform. We thank colleagues at the of Veterinary Science Research Institute (VSRI)-Muguga of
Veterinary Science Research Institute (VSRI)-Muguga of Kenya Agricultural and Livestock Research organization
Kenya Agricultural and Livestock Research Organization (KALRO)
(KALRO), Directorate of Veterinary Services (DVS), and
those from Kajiado county. We also want to thank the REFERENCES
community disease reporters (CDRs), Chiefs, and all
participants who sent the data regularly. Sincer thanks to [1]. Animal Disease Information System (ADIS). (n.d.).
Vincent Odedo, Mohamed Muktar, Leonard Ateya for Retrieved March 25, 2023, from
technical support in the field. https://food.ec.europa.eu/animals/animal-
diseases/animal-disease-information-system-adis_en
[2]. Bangura, F. I., Leno, A., Hann, K., Timire, C., Nair, D.,
Bah, M. A., Gborie, S. R., Satyanarayana, S., Edwards, J.
K., Davtyan, H., Kamara, S. M., Jalloh, A. T., Sellu-

IJISRT23MAY1822 www.ijisrt.com 3262

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
Sallu, D., Kanu, J. S., Johnson, R., & Nantima, N. https://doi.org/10.1007/s10109-021-00368-0
(2022). An Update on the Surveillance of Livestock [12]. Karimuribo, E. D., Mutagahywa, E., Sindato, C.,
Diseases and Antimicrobial Use in Sierra Leone in Mboera, L., Mwabukusi, M., Njenga, M. K., Teesdale,
2021—An Operational Research Study. International S., Olsen, J., & Rweyemamu, M. (2017). A Smartphone
Journal of Environmental Research and Public Health, App (AfyaData) for Innovative One Health Disease
19(9), 1–12. https://doi.org/10.3390/ijerph19095294 Surveillance from Community to National Levels in
[3]. Bedelian, C., & Ogutu, J. O. (2017). Trade-offs for Africa: Intervention in Disease Surveillance. JMIR
climate-resilient pastoral livelihoods in wildlife Public Health Surveill 2017;3(4):E94
conservancies in the Mara ecosystem, Kenya. Https://Publichealth.Jmir.Org/2017/4/E94, 3(4), e7373.
Pastoralism, 7(1), 1–22. https://doi.org/10.1186/S13570- https://doi.org/10.2196/PUBLICHEALTH.7373
017-0085-1/FIGURES/8 [13]. Kenya’s Sheep and Goat Meat Market Report 2023 -
[4]. Bin Tarif, A., Lasecka, L., Holzer, B., & Baron, M. D. Prices, Size, Forecast, and Companies. (n.d.). Retrieved
(2012). Ganjam virus/Nairobi sheep disease virus March 9, 2023, from
induces a pro-inflammatory response in infected sheep. https://www.indexbox.io/store/kenya-sheep-and-goat-
Veterinary Research, 43, 71. meat-market-report-analysis-and-forecast-to-2025/
https://doi.org/10.1186/1297-9716-43-71 [14]. Kenya - Food Security Outlook Update: Sat, 2022-12-31
[5]. Chethan Kumar, H., Hiremath, J., Yogisharadhya, R., | Famine Early Warning Systems Network. (n.d.).
Balamurugan, V., Jacob, S., Manjunatha Reddy, G., Retrieved March 9, 2023, from https://fews.net/east-
Suresh, K., Shome, R., Nagalingam, M., Sridevi, R., africa/kenya/food-security-outlook-update/january-2023
Patil, S., Prajapati, A., Govindaraj, G., Sengupta, P., [15]. Lesmanawati, D. A. S., Veenstra, P., Moa, A., Adam, D.
Hemadri, D., Krishnamoorthy, P., Misri, J., Kumar, A., C., & Macintyre, C. R. (2020). A rapid risk analysis tool
Tripathi, B., & Shome, B. (2021). Animal disease to prioritise response to infectious disease outbreaks.
surveillance: Its importance & present status in India. BMJ Global Health, 5, 2327.
The Indian Journal of Medical Research, 153(3), 299. https://doi.org/10.1136/bmjgh-2020-002327
https://doi.org/10.4103/IJMR.IJMR_740_21 [16]. Livestock Population - Kenya National Bureau of
[6]. Climate change destroys the livelihoods of Kenyan Statistics. (n.d.). Retrieved March 25, 2023, from
pastoralists | Africa Renewal. (n.d.). Retrieved March 9, https://www.knbs.or.ke/livestock-population/
2023, from [17]. Maciej Serda, Becker, F. G., Cleary, M., Team, R. M.,
https://www.un.org/africarenewal/magazine/january- Holtermann, H., The, D., Agenda, N., Science, P., Sk, S.
2023/climate-change-destroys-livelihoods-kenyan- K., Hinnebusch, R., Hinnebusch A, R., Rabinovich, I.,
pastoralists Olmert, Y., Uld, D. Q. G. L. Q., Ri, W. K. H. U., Lq, V.,
[7]. Diuk-Wasser, M. A., Vanacker, M. C., & Fernandez, M. Frxqwu, W. K. H., Zklfk, E., Edvhg, L. V, … ‫فاطمی‬, ‫ح‬.
P. (2021). Impact of Land Use Changes and Habitat (2013). Synteza i aktywność biologiczna nowych
Fragmentation on the Eco-epidemiology of Tick-Borne analogów tiosemikarbazonowych chelatorów żelaza.
Diseases. Journal of Medical Entomology, 58(4), 1546– Uniwersytet Śląski, 7(1), 343–354.
1564. https://doi.org/10.1093/JME/TJAA209 https://doi.org/10.2/JQUERY.MIN.JS
[8]. Florio, W., Baldeschi, L., Rizzato, C., Tavanti, A., [18]. McGreevy, P., Thomson, P., Dhand, N. K.,
Ghelardi, E., & Lupetti, A. (2020). Detection of Raubenheimer, D., Masters, S., Mansfield, C. S.,
Antibiotic-Resistance by MALDI-TOF Mass Baldwin, T., Magalhaes, R. J. S., Rand, J., Hill, P.,
Spectrometry: An Expanding Area. Frontiers in Cellular Peaston, A., Gilkerson, J., Combs, M., Raidal, S., Irwin,
and Infection Microbiology, 10(November), 1–7. P., Irons, P., Squires, R., Brodbelt, D., & Hammond, J.
https://doi.org/10.3389/fcimb.2020.572909 (2017). VetCompass Australia: A National Big Data
[9]. Guernier, V., Milinovich, G. J., Santos, M. A. B., Collection System for Veterinary Science. Animals 2017,
Haworth, M., Coleman, G., & Soares Magalhaes, R. J. Vol. 7, Page 74, 7(10), 74.
(2016). Use of big data in the surveillance of veterinary https://doi.org/10.3390/ANI7100074
diseases: Early detection of tick paralysis in companion [19]. Merianos, A. (2007). Surveillance and response to
animals. Parasites and Vectors, 9(1). disease emergence. Current Topics in Microbiology and
https://doi.org/10.1186/S13071-016-1590-6 Immunology, 315, 477–509. https://doi.org/10.1007/978-
[10]. Hernández-Jover, M., Phiri, B. J., Stringer, L., & 3-540-70962-6_19
Martínez Avilés, M. (2021). Editorial: Developments in [20]. Mremi, I. R., Rumisha, S. F., Sindato, C., Kimera, S. I.,
Animal Health Surveillance. Frontiers in Veterinary & Mboera, L. E. G. (2022). Comparative assessment of
Science, 7, 1233. the human and animal health surveillance systems in
https://doi.org/10.3389/FVETS.2020.637364/BIBTEX Tanzania: Opportunities for an integrated one health
[11]. Jaya, I. G. N. M., & Folmer, H. (2022). Spatiotemporal surveillance platform. Global Public Health, 0(0), 1–17.
high-resolution prediction and mapping: methodology https://doi.org/10.1080/17441692.2022.2110921
and application to dengue disease. Journal of
Geographical Systems, 1–55.

IJISRT23MAY1822 www.ijisrt.com 3263

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
[21]. Mworia, J. K., Kinyamario, J. I., & Githaiga, J. M. [30]. Understanding the socioeconomic impact of Foot-and-
(2008). Influence of cultivation, settlements and water mouth Disease control in Kenya | The Cattle Site. (n.d.).
sources on wildlife distribution and habitat selection in Retrieved March 9, 2023, from
south-east Kajiado, Kenya. Environmental Conservation, https://www.thecattlesite.com/articles/4396/understandin
35(2), 117–124. g-the-socioeconomic-impact-of-foot-and-mouth-disease-
https://doi.org/10.1017/S0376892908004670 control-in-kenya
[22]. Njenga, M. K., Kemunto, N., Kahariri, S., Holmstrom, [31]. Voeten, M. M., & Prins, H. H. T. (1999). Resource
L., Oyas, H., Biggers, K., Riddle, A., Gachohi, J., partitioning between sympatric wild and domestic
Muturi, M., Mwatondo, A., Gakuya, F., Lekolool, I., herbivores in the Tarangire region of Tanzania.
Sitawa, R., Apamaku, M., Osoro, E., Widdowson, M. A., Oecologia, 20(2), 287–294.
& Munyua, P. (2021). High real-time reporting of https://doi.org/10.1007/s004420050860
domestic and wild animal diseases following rollout of [32]. Wu, X., Lu, Y., Zhou, S., Chen, L., & Xu, B. (2016).
mobile phone reporting system in Kenya. PLoS ONE, Impact of climate change on human infectious diseases:
16(9 September), 1–13. Empirical evidence and human adaptation. Environment
https://doi.org/10.1371/journal.pone.0244119 International, 86, 14–23.
[23]. Okello, I., Mafie, E., Eastwood, G., Nzalawahe, J., https://doi.org/10.1016/J.ENVINT.2015.09.007
Mboera, L. E. G., & Onyoyo, S. (2022). Prevalence and [33]. Animal Disease Information System (ADIS). (n.d.).
Associated Risk Factors of African Animal Retrieved March 25, 2023, from
Trypanosomiasis in Cattle in Lambwe, Kenya. Journal of
https://food.ec.europa.eu/animals/animal-
Parasitology Research, 2022.
https://doi.org/10.1155/2022/5984376 diseases/animal-disease-information-system-
[24]. Omondi, G. P., Gakuya, F., Arzt, J., Sangula, A., adis_en
Hartwig, E., Pauszek, S., Smoliga, G., Brito, B., Perez, [34]. Bangura, F. I., Leno, A., Hann, K., Timire, C., Nair, D.,
A., Obanda, V., & VanderWaal, K. (2020). The role of Bah, M. A., Gborie, S. R., Satyanarayana, S., Edwards, J.
African buffalo in the epidemiology of foot-and-mouth K., Davtyan, H., Kamara, S. M., Jalloh, A. T., Sellu-
disease in sympatric cattle and buffalo populations in Sallu, D., Kanu, J. S., Johnson, R., & Nantima, N.
Kenya. Transboundary and Emerging Diseases, 67(5), (2022). An Update on the Surveillance of Livestock
2206–2221. https://doi.org/10.1111/TBED.13573 Diseases and Antimicrobial Use in Sierra Leone in
[25]. Ottichilo, W. K., De Leeuw, J., Skidmore, A. K., Prins, 2021—An Operational Research Study. International
H. H. T., & Said, M. Y. (2000). Population trends of Journal of Environmental Research and Public Health,
large non-migratory wild herbivores and livestock in the 19(9), 1–12. https://doi.org/10.3390/ijerph19095294
Maasai Mara ecosystem, Kenya, between 1979–1997. [35]. Bedelian, C., & Ogutu, J. O. (2017). Trade-offs for
African Journal of Ecology, 38(3), 202–216. climate-resilient pastoral livelihoods in wildlife
https://doi.org/10.1046/j.1365-2028.2000.00242.x conservancies in the Mara ecosystem, Kenya.
[26]. Rosenberg, R. (2015). Detecting the emergence of novel, Pastoralism, 7(1), 1–22. https://doi.org/10.1186/S13570-
zoonotic viruses pathogenic to humans. Cellular and 017-0085-1/FIGURES/8
Molecular Life Sciences, 72(6), 1115–1125. [36]. Bin Tarif, A., Lasecka, L., Holzer, B., & Baron, M. D.
https://doi.org/10.1007/S00018-014-1785-Y (2012). Ganjam virus/Nairobi sheep disease virus
[27]. SONENSHINE, D. E., LANE, R. S., & NICHOLSON, induces a pro-inflammatory response in infected sheep.
W. L. (2002). TICKS ( Ixodida ). Medical and Veterinary Research, 43, 71.
Veterinary Entomology, 517–558. https://doi.org/10.1186/1297-9716-43-71
https://doi.org/10.1016/B978-012510451-7/50026-8 [37]. Chethan Kumar, H., Hiremath, J., Yogisharadhya, R.,
[28]. Thumbi, S. M., Njenga, M. K., Otiang, E., Otieno, L., Balamurugan, V., Jacob, S., Manjunatha Reddy, G.,
Munyua, P., Eichler, S., Widdowson, M. A., McElwain, Suresh, K., Shome, R., Nagalingam, M., Sridevi, R.,
T. F., & Palmer, G. H. (2019). Mobile phone-based Patil, S., Prajapati, A., Govindaraj, G., Sengupta, P.,
surveillance for animal disease in rural communities: Hemadri, D., Krishnamoorthy, P., Misri, J., Kumar, A.,
Implications for detection of zoonoses spillover. Tripathi, B., & Shome, B. (2021). Animal disease
Philosophical Transactions of the Royal Society B: surveillance: Its importance & present status in India.
Biological Sciences, 374(1782). The Indian Journal of Medical Research, 153(3), 299.
https://doi.org/10.1098/rstb.2019.0020 https://doi.org/10.4103/IJMR.IJMR_740_21
[29]. Tyrrell, P., Russell, S., & Western, D. (2017). Seasonal [38]. Climate change destroys the livelihoods of Kenyan
movements of wildlife and livestock in a heterogenous pastoralists | Africa Renewal. (n.d.). Retrieved March 9,
pastoral landscape: Implications for coexistence and 2023, from
community based conservation. Global Ecology and https://www.un.org/africarenewal/magazine/january-
Conservation, 12, 59–72. 2023/climate-change-destroys-livelihoods-kenyan-
https://doi.org/10.1016/J.GECCO.2017.08.006 pastoralists

IJISRT23MAY1822 www.ijisrt.com 3264

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
[39]. Diuk-Wasser, M. A., Vanacker, M. C., & Fernandez, M. Frxqwu, W. K. H., Zklfk, E., Edvhg, L. V, … ‫فاطمی‬, ‫ح‬.
P. (2021). Impact of Land Use Changes and Habitat (2013). Synteza i aktywność biologiczna nowych
Fragmentation on the Eco-epidemiology of Tick-Borne analogów tiosemikarbazonowych chelatorów żelaza.
Diseases. Journal of Medical Entomology, 58(4), 1546– Uniwersytet Śląski, 7(1), 343–354.
1564. https://doi.org/10.1093/JME/TJAA209 https://doi.org/10.2/JQUERY.MIN.JS
[40]. Florio, W., Baldeschi, L., Rizzato, C., Tavanti, A., [50]. McGreevy, P., Thomson, P., Dhand, N. K.,
Ghelardi, E., & Lupetti, A. (2020). Detection of Raubenheimer, D., Masters, S., Mansfield, C. S.,
Antibiotic-Resistance by MALDI-TOF Mass Baldwin, T., Magalhaes, R. J. S., Rand, J., Hill, P.,
Spectrometry: An Expanding Area. Frontiers in Cellular Peaston, A., Gilkerson, J., Combs, M., Raidal, S., Irwin,
and Infection Microbiology, 10(November), 1–7. P., Irons, P., Squires, R., Brodbelt, D., & Hammond, J.
https://doi.org/10.3389/fcimb.2020.572909 (2017). VetCompass Australia: A National Big Data
[41]. Guernier, V., Milinovich, G. J., Santos, M. A. B., Collection System for Veterinary Science. Animals 2017,
Haworth, M., Coleman, G., & Soares Magalhaes, R. J. Vol. 7, Page 74, 7(10), 74.
(2016). Use of big data in the surveillance of veterinary https://doi.org/10.3390/ANI7100074
diseases: Early detection of tick paralysis in companion [51]. Merianos, A. (2007). Surveillance and response to
animals. Parasites and Vectors, 9(1). disease emergence. Current Topics in Microbiology and
https://doi.org/10.1186/S13071-016-1590-6 Immunology, 315, 477–509. https://doi.org/10.1007/978-
[42]. Hernández-Jover, M., Phiri, B. J., Stringer, L., & 3-540-70962-6_19
Martínez Avilés, M. (2021). Editorial: Developments in [52]. Mremi, I. R., Rumisha, S. F., Sindato, C., Kimera, S. I.,
Animal Health Surveillance. Frontiers in Veterinary & Mboera, L. E. G. (2022). Comparative assessment of
Science, 7, 1233. the human and animal health surveillance systems in
https://doi.org/10.3389/FVETS.2020.637364/BIBTEX Tanzania: Opportunities for an integrated one health
[43]. Jaya, I. G. N. M., & Folmer, H. (2022). Spatiotemporal surveillance platform. Global Public Health, 0(0), 1–17.
high-resolution prediction and mapping: methodology https://doi.org/10.1080/17441692.2022.2110921
and application to dengue disease. Journal of [53]. Mworia, J. K., Kinyamario, J. I., & Githaiga, J. M.
Geographical Systems, 1–55. (2008). Influence of cultivation, settlements and water
https://doi.org/10.1007/s10109-021-00368-0 sources on wildlife distribution and habitat selection in
[44]. Karimuribo, E. D., Mutagahywa, E., Sindato, C., south-east Kajiado, Kenya. Environmental Conservation,
Mboera, L., Mwabukusi, M., Njenga, M. K., Teesdale, 35(2), 117–124.
S., Olsen, J., & Rweyemamu, M. (2017). A Smartphone https://doi.org/10.1017/S0376892908004670
App (AfyaData) for Innovative One Health Disease [54]. Njenga, M. K., Kemunto, N., Kahariri, S., Holmstrom,
Surveillance from Community to National Levels in L., Oyas, H., Biggers, K., Riddle, A., Gachohi, J.,
Africa: Intervention in Disease Surveillance. JMIR Muturi, M., Mwatondo, A., Gakuya, F., Lekolool, I.,
Public Health Surveill 2017;3(4):E94 Sitawa, R., Apamaku, M., Osoro, E., Widdowson, M. A.,
Https://Publichealth.Jmir.Org/2017/4/E94, 3(4), e7373. & Munyua, P. (2021). High real-time reporting of
https://doi.org/10.2196/PUBLICHEALTH.7373 domestic and wild animal diseases following rollout of
[45]. Kenya’s Sheep and Goat Meat Market Report 2023 - mobile phone reporting system in Kenya. PLoS ONE,
Prices, Size, Forecast, and Companies. (n.d.). Retrieved 16(9 September), 1–13.
March 9, 2023, from https://doi.org/10.1371/journal.pone.0244119
https://www.indexbox.io/store/kenya-sheep-and-goat- [55]. Okello, I., Mafie, E., Eastwood, G., Nzalawahe, J.,
meat-market-report-analysis-and-forecast-to-2025/ Mboera, L. E. G., & Onyoyo, S. (2022). Prevalence and
[46]. Kenya - Food Security Outlook Update: Sat, 2022-12-31 Associated Risk Factors of African Animal
| Famine Early Warning Systems Network. (n.d.). Trypanosomiasis in Cattle in Lambwe, Kenya. Journal of
Retrieved March 9, 2023, from https://fews.net/east- Parasitology Research, 2022.
africa/kenya/food-security-outlook-update/january-2023 https://doi.org/10.1155/2022/5984376
[47]. Lesmanawati, D. A. S., Veenstra, P., Moa, A., Adam, D. [56]. Omondi, G. P., Gakuya, F., Arzt, J., Sangula, A.,
C., & Macintyre, C. R. (2020). A rapid risk analysis tool Hartwig, E., Pauszek, S., Smoliga, G., Brito, B., Perez,
to prioritise response to infectious disease outbreaks. A., Obanda, V., & VanderWaal, K. (2020). The role of
BMJ Global Health, 5, 2327. African buffalo in the epidemiology of foot-and-mouth
https://doi.org/10.1136/bmjgh-2020-002327 disease in sympatric cattle and buffalo populations in
[48]. Livestock Population - Kenya National Bureau of Kenya. Transboundary and Emerging Diseases, 67(5),
Statistics. (n.d.). Retrieved March 25, 2023, from 2206–2221. https://doi.org/10.1111/TBED.13573
https://www.knbs.or.ke/livestock-population/ [57]. Ottichilo, W. K., De Leeuw, J., Skidmore, A. K., Prins,
[49]. Maciej Serda, Becker, F. G., Cleary, M., Team, R. M., H. H. T., & Said, M. Y. (2000). Population trends of
Holtermann, H., The, D., Agenda, N., Science, P., Sk, S. large non-migratory wild herbivores and livestock in the
K., Hinnebusch, R., Hinnebusch A, R., Rabinovich, I., Maasai Mara ecosystem, Kenya, between 1979–1997.
Olmert, Y., Uld, D. Q. G. L. Q., Ri, W. K. H. U., Lq, V., African Journal of Ecology, 38(3), 202–216.

IJISRT23MAY1822 www.ijisrt.com 3265

Volume 8, Issue 5, May – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
https://doi.org/10.1046/j.1365-2028.2000.00242.x
[58]. Rosenberg, R. (2015). Detecting the emergence of novel,
zoonotic viruses pathogenic to humans. Cellular and
Molecular Life Sciences, 72(6), 1115–1125.
https://doi.org/10.1007/S00018-014-1785-Y
[59]. SONENSHINE, D. E., LANE, R. S., & NICHOLSON,
W. L. (2002). TICKS ( Ixodida ). Medical and
Veterinary Entomology, 517–558.
https://doi.org/10.1016/B978-012510451-7/50026-8
[60]. Thumbi, S. M., Njenga, M. K., Otiang, E., Otieno, L.,
Munyua, P., Eichler, S., Widdowson, M. A., McElwain,
T. F., & Palmer, G. H. (2019). Mobile phone-based
surveillance for animal disease in rural communities:
Implications for detection of zoonoses spillover.
Philosophical Transactions of the Royal Society B:
Biological Sciences, 374(1782).
https://doi.org/10.1098/rstb.2019.0020
[61]. Tyrrell, P., Russell, S., & Western, D. (2017). Seasonal
movements of wildlife and livestock in a heterogenous
pastoral landscape: Implications for coexistence and
community based conservation. Global Ecology and
Conservation, 12, 59–72.
https://doi.org/10.1016/J.GECCO.2017.08.006
[62]. Understanding the socioeconomic impact of Foot-and-
mouth Disease control in Kenya | The Cattle Site. (n.d.).
Retrieved March 9, 2023, from
https://www.thecattlesite.com/articles/4396/understandin
g-the-socioeconomic-impact-of-foot-and-mouth-disease-
control-in-kenya
[63]. Voeten, M. M., & Prins, H. H. T. (1999). Resource
partitioning between sympatric wild and domestic
herbivores in the Tarangire region of Tanzania.
Oecologia, 20(2), 287–294.
https://doi.org/10.1007/s004420050860
[64]. Wu, X., Lu, Y., Zhou, S., Chen, L., & Xu, B. (2016).
Impact of climate change on human infectious diseases:
Empirical evidence and human adaptation. Environment
International, 86, 14–23.
https://doi.org/10.1016/J.ENVINT.2015.09.007

IJISRT23MAY1822 www.ijisrt.com 3266