Pillars for successful operationalization of one health as an ecosystem approach: experience from a human-animal interface in the Maasai steppe in Tanzania.

BACKGROUND: Solving complex public health challenges requires integrated approaches to health, such as One Health. A key element of the One Health approach is the interrelationship between human, animal and environmental health and the associated multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Here we describe a pragmatic approach for One Health operationalisation basing on our long-term engagement with communities faced with health challenges in a human-livestock-wildlife interface in the Maasai steppe in northern Tanzania. METHODS: Using a qualitative study design we performed an outcome mapping to document insights on results integration from our previous project. Data were collected through participatory community meetings, in-depth interviews and field observations. Field notes were coded and analysed using inductive thematic analysis. RESULTS: We found that effective implementation of One Health interventions in complex ecosystems works best by understanding local conditions and their context and by working closely with the local people and relevant disciplinary players as one complex adaptive system. Community engagement, systems analysis, transdisciplinarity as well as political commitment played critical roles in successful operationalization of One Health. We have further emphasized that project ownership is as important to the local community as it is to the researchers. When used in combination, these elements (community engagement, systems analysis, transdisciplinarity) provide essential pillars for co-creation and maintaining collective action to set a common vision across disciplines, serving as inputs for a metrics-based toolbox for One Health operationalisation. CONCLUSION: Considering the novelty and complexity of One Health operationalisation, there is need also to develop scorecard-based guidance for assessment of One Health programs at local and national level. This paper proposes a framework for the optimization of an ecosystems-based One Health approach for prevention and control of Vector-Borne Diseases implemented at the local, sub-national or national level.

Estimating Risk of Introduction of Ebola Virus Disease from the Democratic Republic of Congo to Tanzania: A Qualitative Assessment.

Between April 2018 and November 2020, the Democratic Republic of Congo (DRC) experienced its 11th Ebola virus disease (EVD) outbreak. Tanzania's cross-border interactions with DRC through regular visitors, traders, and refugees are of concern, given the potential for further spread to neighboring countries. This study aimed to estimate the risk of introducing EVD to Tanzania from DRC. National data for flights, boats, and car transport schedules from DRC to Tanzania covering the period of May 2018 to June 2019 were analyzed to describe population movement via land, port, and air travel and coupled with available surveillance data to model the risk of EVD entry. The land border crossing was considered the most frequently used means of travel and the most likely pathway of introducing EVD from DRC to Tanzania. High probabilities of introducing EVD from DRC to Tanzania through the assessed pathways were associated with the viability of the pathogen and low detection capacity at the ports of entry. This study provides important information regarding the elements contributing to the risk associated with the introduction of EBV in Tanzania. It also indicates that infected humans arriving via land are the most likely pathway of EBV entry, and therefore, mitigation strategies including land border surveillance should be strengthened.

Leveraging Sub-national Collaboration and Influence for Improving Animal Health Surveillance and Response: A Stakeholder Mapping in Tanzania.

Animal health surveillance plays a vital role in ensuring public health, animal welfare, and sustainable food production by monitoring disease trends, early detecting (new) hazards, facilitating disease control and infection, and providing data for risk analysis. Good stakeholder collaboration across the sector can lead to better communication, better science and decision-making and more effective surveillance and response. An understanding of relevant stakeholders, their interests and their power can facilitate such collaboration. While information on key stakeholders in animal health surveillance is available at the national level in Tanzania, it is missing at the subnational level. The study aimed to explore the existing stakeholders' collaborations and influences at the subnational level through stakeholder mapping and to determine potential leverage points for improving the national animal health surveillance system. A qualitative design was used, involving consultative workshops with government animal health practitioners in Sumbawanga, Sikonge and Kilombero districts of Tanzania from December 2020 to January 2021. Data were collected using an adapted USAID stakeholder collaboration mapping tool with the following steps: (i) Define the objective (ii) Identify all stakeholders (iii) Take stock of the current relationships (iv) Determine resource-based influence (v) Determine non-resource based influence and (vi) Review and revise the collaboration map. Forty-five stakeholders were identified in all three districts and grouped into four categories: private sector and non-government organizations (n = 16), government (n = 16), community (n = 9) and political leaders (n = 4). Animal health practitioners had a stronger relationship with community stakeholders as compared to other categories. The results also showed that most of the stakeholders have non-resource-based influence compared to resource-based influence. The private sector and non-government organizations have a relatively higher number of resource-based influential stakeholders, while political leaders have more non-resource-based influence. The mapping exercise demonstrated that the system could benefit from community mobilization and sensitization, resource mobilization and expanding the horizon of surveillance data sources. Some of the leverage points include integration of surveillance activities into animal health services, clear operational processes, constant engagement, coordination and incentivization of stakeholders. The diversity in the identified stakeholders across the districts suggests that collaborations are contextual and socially constructed.

Twenty years of integrated disease surveillance and response in Sub-Saharan Africa: challenges and opportunities for effective management of infectious disease epidemics.

INTRODUCTION: This systematic review aimed to analyse the performance of the Integrated Disease Surveillance and Response (IDSR) strategy in Sub-Saharan Africa (SSA) and how its implementation has embraced advancement in information technology, big data analytics techniques and wealth of data sources. METHODS: HINARI, PubMed, and advanced Google Scholar databases were searched for eligible articles. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols. RESULTS: A total of 1,809 articles were identified and screened at two stages. Forty-five studies met the inclusion criteria, of which 35 were country-specific, seven covered the SSA region, and three covered 3-4 countries. Twenty-six studies assessed the IDSR core functions, 43 the support functions, while 24 addressed both functions. Most of the studies involved Tanzania (9), Ghana (6) and Uganda (5). The routine Health Management Information System (HMIS), which collects data from health care facilities, has remained the primary source of IDSR data. However, the system is characterised by inadequate data completeness, timeliness, quality, analysis and utilisation, and lack of integration of data from other sources. Under-use of advanced and big data analytical technologies in performing disease surveillance and relating multiple indicators minimises the optimisation of clinical and practice evidence-based decision-making. CONCLUSIONS: This review indicates that most countries in SSA rely mainly on traditional indicator-based disease surveillance utilising data from healthcare facilities with limited use of data from other sources. It is high time that SSA countries consider and adopt multi-sectoral, multi-disease and multi-indicator platforms that integrate other sources of health information to provide support to effective detection and prompt response to public health threats.

Gendered Social Norms Change in Water Governance Structures Through Community Facilitation: Evaluation of the UPWARD Intervention in Tanzania.

Background: In rural Tanzania, women and girls disproportionately bear the burden of water scarcity. Gendered social norms on the acceptability of women's participation in the public sphere limit their decision-making power within local water governance structures. The UPWARD (Uplifting Women's Participation in Water-Related Decision-Making) intervention sought to understand how a community-based gendered social norms approach using organized diffusion can lead to changes in the gendered social norms impacting women's participation in water-related governance structures. Methods: As part of WARIDI, a 5-years integrated water resource management (IWRM) program, a gendered-social norms change (GSNC) activity (UPWARD: Uplifting Women's Participation in Water-Related Decision-Making) was implemented in two villages in Iringa and Kilombero districts. Encouraging organized diffusion, UPWARD promoted gender-equitable norms among a critical mass of community members. WARIDI identified and trained a Community Facilitation Team (CFT) of three women and men to lead a series of education and empowerment sessions in two communities. The intervention reached >300 individuals directly (∼10% of total village population). Changes in social norms were assessed through social norms analysis plots (SNAP) delivered in focus group discussions (FGDs) of 8-12 participants. Results: At baseline, most participants reported that women's involvement in water-related decision-making was restricted to household decisions. Men viewed themselves as primary decision-makers in water governance. Women who spoke in village meetings experienced sanctions for disrespect and outspokenness; their husbands were teased for being "controlled." At endline, participants reported fewer instances of ridicule towards women's participation. Women expressed a greater sense of solidarity with each other; men reported greater respect for men whose wives contribute. The intervention's effects appeared more pronounced in areas with greater cultural heterogeneity, suggesting norm change may be harder to affect where norms are tighter. Conclusion: UPWARD provides evidence that gendered social norms change programs can have identifiable impacts on women's participation in water-related decision-making over a short time. While other interventions have used larger, multi-level strategies to affect gender norms, UPWARD has shown that community mobilization with brief (∼4 months) but concentrated engagement with communities can promote changes in social norms that persist at least 6 months after intervention's end.

Towards an integrated animal health surveillance system in Tanzania: making better use of existing and potential data sources for early warning surveillance.

BACKGROUND: Effective animal health surveillance systems require reliable, high-quality, and timely data for decision making. In Tanzania, the animal health surveillance system has been relying on a few data sources, which suffer from delays in reporting, underreporting, and high cost of data collection and transmission. The integration of data from multiple sources can enhance early detection and response to animal diseases and facilitate the early control of outbreaks. This study aimed to identify and assess existing and potential data sources for the animal health surveillance system in Tanzania and how they can be better used for early warning surveillance. The study used a mixed-method design to identify and assess data sources. Data were collected through document reviews, internet search, cross-sectional survey, key informant interviews, site visits, and non-participant observation. The assessment was done using pre-defined criteria. RESULTS: A total of 13 data sources were identified and assessed. Most surveillance data came from livestock farmers, slaughter facilities, and livestock markets; while animal dip sites were the least used sources. Commercial farms and veterinary shops, electronic surveillance tools like AfyaData and Event Mobile Application (EMA-i) and information systems such as the Tanzania National Livestock Identification and Traceability System (TANLITS) and Agricultural Routine Data System (ARDS) show potential to generate relevant data for the national animal health surveillance system. The common variables found across most sources were: the name of the place (12/13), animal type/species (12/13), syndromes (10/13) and number of affected animals (8/13). The majority of the sources had good surveillance data contents and were accessible with medium to maximum spatial coverage. However, there was significant variation in terms of data frequency, accuracy and cost. There were limited integration and coordination of data flow from the identified sources with minimum to non-existing automated data entry and transmission. CONCLUSION: The study demonstrated how the available data sources have great potential for early warning surveillance in Tanzania. Both existing and potential data sources had complementary strengths and weaknesses; a multi-source surveillance system would be best placed to harness these different strengths.

Mechanisms and Contextual Factors Affecting the Implementation of Animal Health Surveillance in Tanzania: A Process Evaluation.

A strong animal health surveillance system is an essential determinant of the health of animal and human population. To ensure its functionality and performance, it needs to be evaluated regularly. Therefore, a process evaluation was conducted in this study to assess animal health surveillance processes, mechanisms and the contextual factors which facilitate or hinder uptake, implementation and sustainability of the system in Tanzania. A mixed-method study design was used to evaluate the national animal health surveillance system guided by a framework for process evaluation of complex interventions developed by Moore and others. The system was assessed against standard guidelines and procedures using the following attributes: fidelity, adherence, exposure, satisfaction, participation rate, recruitment and context. Quantitative and qualitative data were collected using a cross-sectional survey, key informant interviews, document review, site visits and non-participant observation. Data from questionnaires were downloaded, cleaned and analyzed in Microsoft™ Excel. Qualitative data were analyzed following deductive thematic and content analysis methods. Fidelity attribute showed that case identification is mainly based on clinical signs due to limited laboratory services for confirmation. Data collection was not well-coordinated and there were multiple disparate reporting channels. Adherence in terms of the proportion of reports submitted per month was only 61% of the target. District-level animal health officials spent an average of 60% of their weekly time on surveillance-related activities, but only 12% of them were satisfied with the surveillance system. Their dissatisfaction was caused by large area coverage with little to no facilitation, poor communication, and lack of a supporting system. The cost of surveillance data was found to be 1.4 times higher than the annual surveillance budget. The timeliness of the system ranged between 0 and 153 days from the observation date (median = 2 days, mean = 6 days). The study pointed out some deviations in animal health surveillance processes from the standard guidelines and their implication on the system's performance. The system could be improved by developing a user-friendly unified reporting system, the active involvement of subnational level animal health officials, optimization of data sources and an increase in the horizon of the financing mechanism.

Years of potential life lost and productivity costs due to premature mortality from six priority diseases in Tanzania, 2006-2015.

BACKGROUND: Mortality statistics are traditionally used to quantify the burden of disease and to determine the relative importance of the various causes of death. Some of the most frequently used indices to quantify the burden of disease are the years of potential life lost (YPLL) and years of potential productive life lost (YPPLL). These two measures reflect the mortality trends in younger age groups and they provide a more accurate picture of premature mortality. This study was carried out to determine YPLL, YPPLL and cost of productivity lost (CPL) due to premature mortality caused by selected causes of deaths in Tanzania. METHODS AND FINDINGS: Malaria, respiratory diseases, HIV/AIDS, tuberculosis, cancers and injuries were selected for this analysis. The number of deaths by sex and age groups were obtained from hospital death registers and ICD-10 reporting forms in 39 public hospitals in Tanzania, covering a period of 2006-2015. The life expectancy method and human capital approach were used to estimate the YPLL, YPPLL and CPL due to premature mortality. During 2006-2015, malaria, HIV/AIDS, tuberculosis, respiratory diseases, HIV+tuberculosis, cancer and injury were responsible for a total of 96,834 hospital deaths, of which 46.4% (n = 57,508) were among individuals in the productive age groups (15-64 years). The reported deaths contributed to 2,850,928 YPLL (female = 1,326,724; male = 1,524,205) with an average of 29 years per death. The average YPLL among females (32) was higher than among males (28). Malaria (YPLL = 38 per death) accounted for over one-third (35%) of the total YPLL. There was a significant increase in YPLL due to the selected underlying causes of death over the 10-year period. Deaths from the selected causes resulted into 1,207,499 YPPLL (average = 21 per death). Overall, HIV/AIDS contributed to the highest YPPLL (323,704), followed by malaria (243,490) and injuries (196,505). While there was a general decrease in YPPLL due to malaria, there was an increase of YPPLL due to HIV/AIDS, respiratory diseases, cancer and injuries during the 10-year period. The total CPL due to the six diseases was US$ 148,430,009 for 10 years. The overall CPL was higher among males than females by 29.1%. Over half (58%) of the losses were due to deaths among males. HIV/AIDS accounted for the largest (29.2%) CPL followed by malaria (17.8%) and respiratory diseases (14.6%). The CPL increased from US$11.4 million in 2006 to US$17.9 million in 2016. CONCLUSIONS: The YPLL, YPPLL and CPL due to premature death associated with the six diseases in Tanzania are substantially high. While malaria accounted for highest YPLL, HIV/AIDS accounted for highest YPPLL and CPL. The overall CPL was higher among males than among females. Setting resource allocation priorities to malaria, HIV/AIDS and respiratory diseases that are responsible for the majority of premature deaths could potentially reduce the costs of productivity loss in Tanzania.

A systematic review on integration mechanisms in human and animal health surveillance systems with a view to addressing global health security threats.

BACKGROUND: Health surveillance is an important element of disease prevention, control, and management. During the past two decades, there have been several initiatives to integrate health surveillance systems using various mechanisms ranging from the integration of data sources to changing organizational structures and responses. The need for integration is caused by an increasing demand for joint data collection, use and preparedness for emerging infectious diseases. OBJECTIVE: To review the integration mechanisms in human and animal health surveillance systems and identify their contributions in strengthening surveillance systems attributes. METHOD: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) 2015 checklist. Peer-reviewed articles were searched from PubMed, HINARI, Web of Science, Science Direct and advanced Google search engines. The review included articles published in English from 1900 to 2018. The study selection considered all articles that used quantitative, qualitative or mixed research methods. Eligible articles were assessed independently for quality by two authors using the QualSyst Tool and relevant information including year of publication, field, continent, addressed attributes and integration mechanism were extracted. RESULTS: A total of 102 publications were identified and categorized into four pre-set integration mechanisms: interoperability (35), convergent integration (27), semantic consistency (21) and interconnectivity (19). Most integration mechanisms focused on sensitivity (44.1%), timeliness (41.2%), data quality (23.5%) and acceptability (17.6%) of the surveillance systems. Generally, the majority of the surveillance system integrations were centered on addressing infectious diseases and all hazards. The sensitivity of the integrated systems reported in these studies ranged from 63.9 to 100% (median = 79.6%, n = 16) and the rate of data quality improvement ranged from 73 to 95.4% (median = 87%, n = 4). The integrated systems were also shown improve timeliness where the recorded changes were reported to be ranging from 10 to 91% (median = 67.3%, n = 8). CONCLUSION: Interoperability and semantic consistency are the common integration mechanisms in human and animal health surveillance systems. Surveillance system integration is a relatively new concept but has already been shown to enhance surveillance performance. More studies are needed to gain information on further surveillance attributes.