Stakeholder Analysis for One-Health Preparedness and Operationalization in Kenya: The One-Health Scorecard Approach

doi:10.21203/rs.3.rs-4350683/v1

Background: Rift Valley Fever (RVF) is a climate-sensitive mosquito-borne zoonotic disease with the potential to cause major economic losses due to its high mortality rate in domestic animals including cattle, sheep, goats, and camels. Disease outbreaks are closely associated with climate-driven ecosystem changes that modify interfaces between animals, humans, and the ecosystem. This study evaluated Baringo County, an administrative county in the Rift Valley of Kenya, to determine its preparedness to implement the One-Health Approach (OHA) to combat Rift Valley Fever.

Methods: A cross-sectional study design was used to interview 31 officers from One Health-related government departments in Baringo County. A structured questionnaire based on a One-Health (OH) scorecard system was used to interrogate four components of One-Health. These included capacity, intervention science, risk management, and impact. A binary characterization of the responses was used to assign affirmative responses corresponding to good intervention practices a value of 1 and negative responses a value of zero. Chi-square tests of association were used to determine the associations between existing intervention practices and OHA preparedness.

Results: The study established that Baringo County lacked a structured governance system for operationalizing OHA activities. This was characterized by poor organizational culture and insufficient resource allocation. There was no coordinated implementation of interventions between the different sectors, no implementation research to assess the efficiency of interventions, and no systems analysis within OHA interfaces. The County was, therefore, not resilient to environmental drivers of RVF and had weak risk mitigation strategies in the three One-Health interfaces that include animal, human, and ecosystems. RVF risk potential was determined to be highest in the previous RVF hotspots where its impact was severe.

Conclusion: Baringo County lacks the preparedness for operationalizing the OHA in controlling RVF outbreaks. Based on these findings, the paper recommends: 1) The establishment of a County One-Health Unit comprising interdisciplinary experts from relevant sectors, 2) Capacity building to enhance OHA preparedness, 3) A continuous systems analysis to identify vulnerabilities and changes in the three One Health interfaces and 4) Integrated multisectoral planning and intervention against RVF threat.

Rift Valley Fever

climate change

One-Health

Baringo County

One-Health Approach (OHA) is “a collaborative, multisectoral and transdisciplinary intervention aimed at achieving optimal health and well-being outcomes. It recognizes the interconnectedness between people, animals, plants and their shared environment” (1) The working principles of OHA involve processes which include systems thinking, problem reconceptualization, and fostering transdisciplinarity (1). Systems thinking recognizes that whole entities are comprised of interacting parts with properties that are more than the simple sum of multiple parts(2). Applied to One-Health, it integrates knowledge from agriculture, health, ecology, economics, and political and social systems among others. Due to the complexity of One-Health challenges, it is necessary to involve actors from different sectors to jointly rethink, reconceptualize, reframe issues, and seek robust solutions (3). The transdisciplinarity approach transcends methods of knowledge production occurring solely within disciplinary boundaries as problems do not adhere to such restrictions (4). It brings together stakeholders from diverse disciplines and other (in)directly concerned individuals, such as community members, politicians, and funding agencies (3). For example, rabies control interventions need collaborative planning and implementation from experts in human health, animal health, environmental health, governments, rabies intervention funders, and dog-owning communities (5).

Since OHA is dependent on multiple stakeholders, it is important to leverage on the capacities of each partner. A stakeholder analysis can be used to generate knowledge about each actor’s capacities, vulnerabilities, interactions, and how these affect interventions (6). This information can then be used to enhance collaboration between stakeholders, develop management strategies, and facilitate planning and implementation of interventions. For example, a stakeholder analysis of the multisectoral collaboration towards OHA in RVF control in Kenya revealed that there is more collaboration at the national level than the sub-national level (7), implying that OHA implementation is weak at the sub-national level making OHA ineffective at prevention and control of disease outbreaks.

Building upon the work by Kimani et al. (7), this study sought to undertake a stakeholder analysis at the sub-national level using Baringo County as a case. The stakeholder analysis aimed to assess the County’s preparedness and capacity for operationalizing OHA, guided by a balanced scorecard adopted from the Global Health Group International (8).

The stakeholder analysis in this study focused on government officials from the state departments of medical/public services, livestock development, environment and climate change as well as wildlife from the four sub-county administrative units of Baringo Central, Baringo North, Baringo South, and Tiaty.

A cross-sectional study using a survey that involved collecting data from stakeholders using a semi-structured questionnaire. The questionnaire was based on four interacting domains of a One-Health scorecard namely; capacity, intervention science, risk management, and disease risk and impact which determine the successes of each other (Figure 1). Each domain comprised components whose metrics interrogated the implementing agencies’ OH intervention preparedness. The capacity domain assessed the intervening agencies’ ability to implement OHA. It had three components that assessed the governance structure, organization culture, and resource allocation towards OHA. The intervention science domain assessed the intervening agency’s planning, implementation, monitoring evaluation, and learning capabilities. It had three components that assessed intervention management, implementation research, and a systems analysis. The risk management domain assessed resilience, mitigation practices, and risk control infrastructure. It had three components that assessed preparedness in the social (human), animal, and ecosystem interfaces of One-Health. The fourth domain had one component that assessed the severity, frequency, and risk potential of zoonotic diseases.

Site Description:

The study was carried out in Baringo County in the sub-counties of Baringo Central, Baringo North, Baringo South, and Tiaty. Baringo County is a semi-arid administrative area in the North Rift Valley of Kenya. It is located between 35.602°E, 36.277°E and 0.541°N, 0.723°N and at an altitude ranging between 870 and 2499 m above sea level (asl). The County covers 10,0976 km² with an estimated population of 666,763 as at the 2019 census (9). Baringo County is within the Arid and Semi-Arid Lands (ASALs) of Kenya. The main economic activities are pastoralism in most parts of the County and irrigation agriculture in Baringo South sub-County. This area is prone to both human and animal vector borne diseases such as malaria (10), leishmaniasis (11), brucellosis (12) and Rift Valley Fever (RVF) (13). The last RVF outbreak occurred between the years 2006-2007, causing 5 human deaths (13) and massive economic losses occasioned by livestock deaths (14). The study was carried out in Baringo County because the project had previously implemented a One-Health study and therefore had pre-existing working relations with County departments of health, livestock development and environment and climate change.

Sampling techniques:

A multistage sampling technique was conducted. Respondents were sampled from the County headquarters and Baringo Central, Baringo North, Baringo South (now Marigat) and Tiaty (now Tiaty West) sub-counties. The sampling was stratified to include respondents from the departments of human health, livestock development, environment and climate change, and social services. An initial survey was conducted followed by a workshop where stakeholders discussed and validated the findings after data analysis. A total of 31 officers participated in the stakeholder analysis survey and 19 participated in the stakeholder validation workshop to critique the survey findings. During the validation, officers from departments of wildlife and meteorology were included. The research team captured verbal critique made on the findings and used it to present stakeholder views incorporated in this paper.

Data Analysis:

In each of the components, study respondents answered a set of questions measuring the contribution of variables to OHA preparedness (Appendix 1). The questions in each section were used as predictors of OHA preparedness. For each component, the number of responses indicating OHA preparedness by each respondent was summed up. If affirmative responses exceeded half of the total number of questions, the respondents were awarded a score of 1 to indicate OHA preparedness, while those who did not were awarded a score of 0 to indicate lack of OHA preparedness. Overall, OHA preparedness for each component was determined by summing up the component’s binary categorization in each domain. For each domain, a chi-square test was performed to determine associations between predictor variables and OHA preparedness. Significance levels were set at p<0.05.

The finding of the stakeholders’ analysis is presented based on the One-Health Scorecard’s perspectives and subcomponents.

OHA implementation capacity

Results on the association of variables with OH preparedness in the three sections under the capacity perspective are presented with respective Crammer’s V and Fisher’s p values (Table 1). 78% of the respondents acknowledged that Baringo County did not have good OH governance structure. The lack of a OH Policy and a OH communication strategy was strongly associated with the poor OH governance structure (p<0.001). Non-inclusion of the local community in OH ad hoc committees was also determined to be associated with the lack of a proper OH governance structure (p=0.036).

54% of the respondents acknowledged that OH implementing agencies had a good organizational culture which was found to be strongly associated with existing coordination between implementing departments (p<0.001), sharing of knowledge and experiences across OH relevant sectors (p<0.001), development of new policies based on knowledge acquired from experiences (p<0.001) and engagement of local communities in intervention activities (p<0.001).

Only 1 out of the 50 respondents indicated that human resources, supplies and equipment, and budgetary allocation were adequate for OH implementation. The lack of preparedness in this section was mainly due to lack of sufficient budgetary allocations (p=0.021)

Table 1: Associations between variables and lack of OHA preparedness in Baringo County. Variables with a p-value of <0.05 are significantly associated with OHA preparedness.

Section	Variable	X²	df	Crammer’s V	Fisher’s p
Governance	One Health policy	20.282	2	0.637	<0.001
	OH communication strategy	27.756	2	0.745	<0.001
	OH committee	4.032	3	0.284	0.256
	Inclusion of local community	7.615	2	0.390	0.036
Organizational culture	Coordination between departments	22.125	3	0.665	<0.001
	Knowledge and experience sharing	25.932	2	0.720	<0.001
	New policies	18.534	2	0.609	<0.001
	Local community engagement	29.127	2	0.764	<0.001
Allocation of resources	Human resource	11.735	2	0.484	0.122
	Supplies and equipment	24.490	2	0.700	0.085
	Budgetary allocation	50.0	2	1.0	0.021

OHA Intervention Science

In this domain, the study looked at the influence of intervention management, implementation research, and systems analysis on OHA intervention science. The associations of predictor variables and OHA preparedness in each section are presented below (Table 2). Up to 62% of the respondents indicated that interventions against RVF in Baringo County were not aligned to good intervention management practices. The lack of joint planning (p<0.001), joint implementation (p<0.001), and adaptation of intervention strategies to contextual changes (p<0.001) were strongly associated with weak intervention management (Table 2).

Table 2: Associations between variables and weak intervention science systems in Baringo County. Variables with a p-value of <0.05 are significantly associated with OHA preparedness.

Section	Variables	X²	DF	Crammer’s V	Fisher’s p
Intervention management	Joint planning	26.697	2	0.731	p<0.001
	Joint implementation	28.565	2	0.756	p<0.001
	Adaptation of interventions	27.723	2	0.745	p<0.001
Implementation research	Ongoing research	7.863	2	0.397	p = 0.02
	Tested and evaluated	24.260	2	0.697	p<0.001
	Acceptance, adoption and fidelity	25.349	2	0.712	p<0.001
	Resource efficiency	27.281	2	0.739	p<0.001
	Applied to >1 VBD in both humans and animals	31.231	2	0.790	p<0.001
	Applicable across diverse geographic regions	10.436	2	0.457	p=0.010
	Feasibility, appropriateness and cost	16.119	2	0.568	p=0.001
Systems analysis	Social systems	16.733	2	0.578	p<0.001
	Animal systems	20.048	2	0.633	p<0.001
	Ecosystem	28.096	2	0.750	p<0.001

66% of the respondents indicated that there were no ongoing implementation research activities to evaluate the success of interventions against RVF. This is evident from the lack of ongoing research activities, non-testing and evaluation of interventions in the local context, non-evaluation of interventions’ resource efficiency, no common intervention efforts against RVF in both humans and animals across geographic zones and non-investigation of interventions’ feasibility, appropriateness and cost efficiency (Table 2). The association of these variables with the weak implementation research were all statistically significant.

72% of the respondents indicated that there was no ongoing systems analysis being conducted. The lack of OH risk assessments in the animal-human, human–environment and animal-environment interfaces is strongly associated with the weak systems analysis (Table 2)

OHA risk management

This perspective assessed the resilience, mitigation practices, and risk control infrastructure available in the human, animal, and ecosystem interfaces. The associations of predictor variables to OHA preparedness are presented below (Table 3). Up to 68% of the respondents indicated that there is no resilience against RVF in the social interface.

Table 3: Associations between variables and weak intervention science systems in Baringo County. Variables with a p-value of <0.05 are significantly associated with OHA preparedness.

Section	Variables	X²	DF	Crammer’s V	Fisher’s p
Social systems	Resilience	20.415	1	0.684	p <0.001
	Risk mitigation	17.384	1	0.636	p <0.001
	Risk control	22.018	1	0.707	p <0.001
Animal systems	Resilience	13.654	1	0.566	p <0.001
	Risk mitigation	30.473	1	0.825	p <0.001
	Risk control	30.653	1	0.826	p <0.001
Ecosystems	Resilience	8.459	1	0.461	p =0.001
	Risk mitigation	32.934	1	0.852	p <0.001
	Risk /vector control	0.320	1	0.010	p=0.572

Up to 65% of the respondents indicated that risk management in the social and animal systems was weak. This was attributed to the weak association between resilience (p <0.001), poor risk mitigation (p <0.001), and risk control (p <0.001) in the social and animal systems (Table 3). There was a strong association between risk control and risk management in the ecosystem (p=0.572). All the respondents acknowledged that there is sustainable vector control in the ecosystems that targets all life cycle stages of the vectors. However, the association between ecosystem resilience and integrity was weak (Table 3).

RVF Impact and Risk

This perspective investigated the severity, frequency, and risk potential. Up to 58% of the respondents acknowledged that although the frequency of RVF outbreaks was seasonal and rare, the risk potential was high and whenever outbreaks occurred, they had a high impact. This is shown by the strong associations between OHA preparedness and RVF severity, frequency, and risk potential (Table 4).

Table 4: Associations between variables and RVF impact and risk in Baringo County. Variables with a p-value of <0.05 are significantly associated with OHA preparedness.

Section	Variables	X²	DF	Crammer’s V	Fisher’s p
Impact and Risk	RVF severity	20.415	1	0.684	P<0.001
	RVF frequency	17.384	1	0.636	P<0.001
	RVF risk potential	22.018	1	0.707	P<0.001

Baringo County One Health Score Card Rating

In each section, the number of affirmative (yes) answers were summed up and expressed as a percentage. This value was used as a measure of preparedness in the score card. For example, the governance section had four questions answered by 50 respondents. This gave a total of 200 answers out of which 50 were affirmative, giving 25% affirmative answers. The final score was obtained by expressing the percentages as a part of ten. Nine out of the twelve sections assessed scored below the mean score of 5 on the rating scale and are shown below (Table 5).

Table 5: One Health score card indicating section scores.

Perspective	Section	Yes	Others	Total	% Yes	OH score
Capacity	Governance	50	150	200	25.0	2.5
	Organization	86	64	150	57.3	5.7
	Resources	7	143	150	4.7	0.5
Intervention Science	Intervention Management	58	92	150	38.7	3.9
	Implementation Research	209	191	400	52.3	5.2
	Systems Analysis	21	129	150	14.0	1.4
Risk Management	Social Systems	200	250	450	44.4	4.4
	Animal Systems	90	210	300	30.0	3.0
	Ecosystems	138	212	350	39.4	3.9
Impact and Risk	RVF - Severity	25	25	50	50.0	5.0
	RVF - Frequency	26	24	50	52.0	5.2
	RVF - Risk Potential	18	32	50	36.0	3.6

Under the capacity domain, governance and resource allocation scored below the mean score of 5 indicating that the Baringo County does not have the required OH governance structure and enough resources dedicated towards OHA. Two components of the intervention science perspective namely intervention management and systems analysis scored 3.9 and 1.4 respectively, indicating that they are not at the level needed for OHA operationalization. All risk management components scored below the mean score. RVF severity and frequency scored 5 and 5.2 respectively indicating that RVF outbreaks have an impact on the local community. However, RVF risk potential in Baringo County is low with a score of 3.6. The low RVF risk potential is due to the fact that RVF outbreaks are seasonal and the inter-epidemic periods vary in length, and therefore, lack of knowledge among the respondents interviewed may have affected the findings.

CAPACITY

Operationalization of OHA requires a proper governance and infrastructure within the implementing organization, human resource capacity building, and sufficient supply of technical and financial resources (2). Crucial to governance is the existence of policies to guide One-Health operationalization. This study found out that Baringo County does not have a One-Health policy or a One-Health communication strategy. The Kenya One-Health Strategic Plan for the prevention and control of zoonotic diseases (15) was released in 2021 and is currently being rolled out to the county units. As such One-Health governance structures are yet to be established in the county administrative units, including Baringo County.

Communication, coordination and collaboration (3Cs) between health-related sectors is key in maintaining the multisectoral approach in One-Health implementation (16). This was found to exist in Baringo County where staff in health-related sectors acknowledged that there was information sharing between departments and the local communities during interventions against outbreaks. Benefits of the 3Cs include mainstreaming standard operating procedures for detection and response, surveillance and notification systems for diseases, joint planning and implementation and multisectoral communication during a response, all leading to effective interventions (17). Likewise, implementing sectors evaluate and adapt intervention strategies to suit contextual changes. The organizational cultures in Baringo County is essential for successful operationalization of OHA.

Resource allocation is a major drawback for successful operationalization of OHA in Baringo County. The study found out that human resource is a major challenge as many departments in health-related sectors are understaffed, especially the veterinary department. Due to the low human resource capacity, no staff from the health-related sectors are entirely engaged on One-Health activities. Also critical was limited financial and technical resources to support planning and implementation of interventions.

INTERVENTION SCIENCE

Intervention science is key to monitoring the success of intervention strategies against diseases. Operationalization of OHA thus requires a strong intervention science component to assess intervention successes. Management of interventions require proper planning and implementation. In Baringo County, planning and implementation of interventions is not multi-sectoral and as such does not meet the OHA threshold. Instances of joint planning and implementation have been carried out in the past between the health and veterinary departments in response to RVF and rabies outbreaks. Other important departments in OHA’s multisectoral approach like environment and meteorology are not routinely incorporated.

Implementation research is a new concept that is not yet appreciated by implementing agencies in Baringo and their staff have not yet grasped the concepts. In the few instances where staff alluded to carrying out implementation research, they were referring to collaborations between their departments and external research partners. The lack of implementation research hampers the monitoring and evaluation of interventions and leads to little knowledge of the success and sustainability of interventions. This was confirmed by less than half of the study respondents acknowledging that intervention strategies used to mitigate outbreaks of vector-borne diseases were effective. There is little knowledge on resource efficiency and sustainability of interventions in Baringo County due to a lack of implementation research.

Systems analysis is needed to assess the risk potential of disease threat and requires a detailed analysis of the human, animal, and environment subsystems, their interfaces, and the inherent transmission dynamics. However, systems analysis is not routinely conducted by actors in health-related fields, leading to missed opportunities in detecting disease risks in the human, animal, and environmental interfaces.

RISK MANAGEMENT

Risk management in the human interface

The level of resilience against malaria and RVF in Baringo County is not the same. Mitigation efforts against malaria have increased the community’s resilience. This stems from a high level of awareness of its cause, prevention of transmission, and effective treatment. On the contrary, the level of awareness about RVF among members of the local community is low. Differences in resilience against malaria and RVF can also be attributed to the resources invested in the surveillance, reporting, and intervention against the two diseases. More resources are invested towards malaria control than RVF control.

Risk management in the animal interface

There is a low level of resilience to livestock diseases. This is attributed to a lack of veterinary support. The few veterinary officers in the county are not able to effectively conduct disease surveillance, diagnose and treat animal diseases across the expansive county. Farmers are thus forced to mitigate and treat animal disease yet they are not trained on livestock disease risk and management.

Risk management in the environment interface

Baringo County is part of the arid and semi-arid lands (ASALs) of Kenya. The climate in these regions is characterized by low rainfall and high temperatures which are bound to be exacerbated by the projected climate change. Currently, there are few initiatives being undertaken to conserve the landscape and biodiversity within the County. One of the initiatives was the introduction of Prosopis Juliflora to help stem soil erosion which has resulted in diverging effects. Although it has managed to curb soil erosion, it is invasive in nature and has covered ground that was previously grazing land. It also offers resting ground for mosquitoes and increases the threat of vector borne disease transmission. This increases the vulnerabilities of local communities to disease threats emerging from the loss of habitat integrity.

Vector control

The study found out that there are adequate vector control strategies against mosquitoes. However, the methods being used target malaria vectors that are mainly indoor biting mosquitoes. At individual level, the local community use bednets, burn cow dung and green twigs, clear excess vegetation and drain stagnant water around households. Although these methods are economical, environmentally friendly and sustainable, they are geared towards indoor biting mosquitoes. Majority of the households used vector control methods targeting adult mosquitoes only, which does not stop emergence of new vector populations, especially after seasonal rains.

The findings of this study established general lack of preparedness in operationalizing OHA in Baringo County. This is attributed to a weak implementation capacity stemming from lack of OH governance structure, poor organizational culture and lack of budgetary allocation toward OH activities. Interventions against disease outbreaks are not fully supported by principles of intervention science as evidenced by weak intervention management, lack of implementation research and a weak systems analysis to identify vulnerabilities at the human-animal and ecosystem interfaces. This caused challenges to risk management as there are no interventions designed to increase resilience and risk mitigation in the One Health human-animal-ecosystem interfaces. However, there were significant vector control efforts in the ecosystem interphase based on mosquito control efforts that mainly targeted malaria vectors. Despite the huge impact of RVF attributed to loss of livestock, its impact and risk potential is considered to be low due to the low frequency of outbreaks. The weak OHA operationalization however, can result in huge impacts if the frequency of RVF outbreaks increase. The study recommends the strengthening of Baringo County’s OHS operationalization capacity through the establishment of a County One-Health Unit (COHU) supported by increased budgetary allocations. It also recommends strengthening intervention management, adoption of implementation research and constant systems analysis at the OH interphases to improve OHA risk management.

ASAL

Arid and Semi-Arid Lands

COHU

County One Health Units

OH

One Health

OHA

One Health Approach

RVF

Rift Valley Fever

Ethics approval and consent to participate

The study was approved by the Jaramogi Oginga Odinga University of Science and Technology Ethical Review Committee (ERC /04/2023 (11)). Study participants were informed about the objective of the study and written informed consent was obtained from each respondent. All the information obtained was and will be held confidential and was and will be used only for this study’s purpose.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare no competing interests.

Funding

This research is funded by a grant from the World Health Organization for piloting the draft plan for operationalizing One Health (WHO reference 2020/1047496-2).

Authors' contributions

Conceptualization: BE, EM, AO, GO, CO, JO and DO[1]; Data curation: AO and EM; Formal analysis: AO, EM, BE; Writing-original draft: AO, EM; Writing-review and editing: BE, EM, AO, DO[2], GO, CO, JO, DO¹, DO[3] and IKN; Supervision: BE and IKN

Acknowledgments

The authors acknowledge Mr Haron Bowen for his coordination and logistical support during the study. We also wish to acknowledge the following departments of the Baringo County government for their support during the study: the Directorate of Livestock Production, the Directorate of Medical Services, the Directorate of Preventive and Promotive Health, and the Directorate of Environment and Climate Change.

[1] Daniel Olago

[2] Damar Osok

[3] Dismas Ongore

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No competing interests reported.

APPENDIX1.docx

Stakeholder Analysis for One-Health Preparedness and Operationalization in Kenya: The One-Health Scorecard Approach

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Abstract

Figures

BACKGROUND

METHODS

RESULTS

DISCUSSION

CONCLUSION

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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