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This literature review provides an overview of use of environmental samples (ES) such as faeces, water, air, mud and swabs of surfaces in avian influenza (AI) surveillance programs, focussing on effectiveness, advantages and gaps in knowledge. ES have been used effectively for AI surveillance since the 1970s. Results from ES have enhanced understanding of the biology of AI viruses in wild birds and in markets, of links between human and avian influenza, provided early warning of viral incursions, allowed assessment of effectiveness of control and preventive measures, and assisted epidemiological studies in outbreaks, both avian and human. Variation exists in the methods and protocols used, and no internationally recognized guidelines exist on the use of ES and data management. Few studies have performed direct comparisons of ES versus live bird samples (LBS). Results reported so far demonstrate reliance on ES will not be sufficient to detect virus in all cases when it is present, especially when the prevalence of infection/contamination is low. Multiple sample types should be collected. In live bird markets, ES from processing/selling areas are more likely to test positive than samples from bird holding areas. When compared to LBS, ES is considered a cost‐effective, simple, rapid, flexible, convenient and acceptable way of achieving surveillance objectives. As a non‐invasive technique, it can minimize effects on animal welfare and trade in markets and reduce impacts on wild bird communities. Some limitations of environmental sampling methods have been identified, such as the loss of species‐specific or information on the source of virus, and taxonomic‐level analyses, unless additional methods are applied. Some studies employing ES have not provided detailed methods. In others, where ES and LBS are collected from the same site, positive results have not been assigned to specific sample types. These gaps should be remedied in future studies.

Objectives Hoping to improve health-related effectiveness, a two-phase vaccination against rabies was designed and executed in northern Tanzania in 2018, which included geo-epidemiological and economic perspectives. Methods Considering the local bio-geography and attempting to rapidly establish a protective ring around a city at risk, the first phase intervened on sites surrounding that city, where the population density was lower than in the city at risk. The second phase vaccinated a rural area. Results No rabies-related case has been reported in the vaccinated areas for over a year post-immunisation; hence, the campaign is viewed as highly cost-effective. Other metrics included: rapid implementation (concluded in half the time spent on other campaigns) and the estimated cost per protected life, which was 3.28 times lower than in similar vaccinations. Conclusions The adopted design emphasised local bio-geographical dynamics: it prevented the occurrence of an epidemic in a city with a higher demographic density than its surrounding area and it also achieved greater effectiveness than average interventions. These interdisciplinary, policy-oriented experiences have broad and immediate applications in settings of limited and/or time-sensitive (expertise, personnel, and time available to intervene) resources and conditions.

Objectives We applied a novel Outbreak Costing Tool (OCT), developed by the US Centers for Disease Control and Prevention (CDC), to estimate the costs of investigating and responding to an anthrax outbreak in Tanzania. We also evaluated the OCT's overall utility in its application to a multisectoral outbreak response. Methods We collected data on direct costs associated with a human and animal anthrax outbreak in Songwe Region (December 2018 to January 2019) using structured questionnaires from key-informants. We performed a cost analysis by entering direct costs data into the OCT, grouped into seven cost categories: labor, office, travel and transport, communication, laboratory support, medical countermeasures, and consultancies. Results The total cost for investigating and responding to this outbreak was estimated at 102,232 United States dollars (USD), with travel and transport identified as the highest cost category (62,536 USD) and communication and consultancies as the lowest, with no expenditure, for the combined human and animal health sectors. Conclusions Multisectoral investigation and response may become complex due to coordination challenges, thus allowing escalation of public health impacts. A standardized framework for collecting and analysing cost data is vital to understanding the nature of outbreaks, in anticipatory planning, in outbreak investigation and in reducing time to intervention. Pre-emptive use of the OCT will also reduce overall and specific (response period) intervention costs for the disease. Additional aggregation of the costs by government ministries, departments and tiers will improve the use of the tool to enhance sectoral budget planning for disease outbreaks in a multisectoral response., Highlights • Direct cost estimation for a human-animal anthrax outbreak in Tanzania during 2018–2019, using a novel Outbreak Costing Tool; • Application of a standardized Outbreak Costing Tool facilitates One Health and encourages multisectoral collaboration; • Multisectoral outbreak costing data informs planning against disease outbreaks, such as Rift Valley fever, zoonotic influenza and rabies.

Objectives One Health is transiting from multidisciplinary to transdisciplinary concepts and its viewpoints should move from ‘proxy for zoonoses’, to include other topics (climate change, nutrition and food safety, policy and planning, welfare and well-being, antimicrobial resistance (AMR), vector-borne diseases, toxicosis and pesticides issues) and thematic fields (social sciences, geography and economics). This work was conducted to map the One Health landscape in Africa. Methods An assessment of existing One Health initiatives in Sub-Saharan African (SSA) countries was conducted among selected stakeholders using a multi-method approach. Strengths, weaknesses, opportunities and threats to One Health initiatives were identified, and their influence, interest and impacts were semi-quantitatively evaluated using literature reviews, questionnaire survey and statistical analysis. Results One Health Networks and identified initiatives were spatiotemporally spread across SSA and identified stakeholders were classified into four quadrants. It was observed that imbalance in stakeholders' representations led to hesitation in buying-in into One Health approach by stakeholders who are outside the main networks like stakeholders from the policy, budgeting, geography and sometimes, the environment sectors. Conclusion Inclusion of theory of change, monitoring and evaluation frameworks, and tools for standardized evaluation of One Health policies are needed for a sustained future of One Health and future engagements should be outputs- and outcomes-driven and not activity-driven. National roadmaps for One Health implementation and institutionalization are necessary, and proofs of concepts in One Health should be validated and scaled-up. Dependence on external funding is unsustainable and must be addressed in the medium to long-term. Necessary policy and legal instruments to support One Health nationally and sub-nationally should be implemented taking cognizance of contemporary issues like urbanization, endemic poverty and other emerging issues. The utilization of current technologies and One Health approach in addressing the ongoing pandemic of COVID-19 and other emerging diseases are desirable. Finally, One Health implementation should be anticipatory and preemptive, and not reactive in containing disease outbreaks, especially those from the animal sources or the environment before the risk of spillover to human., Highlights • One Health transcends multidisciplinary and transdisciplinary concepts; it’s expanding scope to cover ignored fields; • Mapping the One Health landscape in Africa is desirable for effective monitoring and evaluation, and measurable outcomes; • Development of national roadmaps is necessary for One Health institutionalization and to develop targeted activities; • Anticipatory and not reactive One Health implementation optimizes its benefits at addressing countries’ challenges.

An evaluation of emerging issues in One Health (OH) in Sub-Saharan Africa was undertaken to map the existing OH initiatives in Sub-Saharan African (SSA) countries. Desk review, expert opinions survey, limited interviews and wider consultations with selected OH stakeholders were conducted. The strengths, weaknesses, opportunities and threats to OH initiatives were identified. OH influence, interest and impacts were evaluated. One Health is transiting from multidisciplinary to transdisciplinary concepts and OH viewpoint should move from ‘proxy for zoonoses’, to include issues of climate change, nutrition and food safety, social sciences, geography, policy and planning, economics, welfare and well-being, antimicrobial resistance (AMR), vector-borne diseases, toxicosis and pesticides issues. While the identified major strengths should be boosted, the weaknesses should be addressed.OH Networks in SSA were spatially and temporally spread across SSA and stakeholders were classified as key, latent, marginal and OH defenders. Imbalance in stakeholders’ representation led to hesitation in buying-in from stakeholders who are outside the main networks. Theory of change, monitoring and evaluation frameworks, and tools to standardized evaluation of OH policies is needed for sustained future of OH and the future OH engagement should be outputs and outcomes-driven and not activity-driven.National roadmap for OH implementation and institutionalization is necessary and proofs of concepts in OH should be verified and scaled-up. Dependence on external funding is unsustainable and must be addressed. Necessary policy and legal instrument to support OH nationally and sub-nationally should be implemented taking cognizance of contemporary issues like urbanization, endemic poverty and other emerging issues. Utilizing current technologies and OH approach to address ongoing pandemic of COVID-19 and other emerging diseases is desirable. Finally, OH implementation should be anticipatory and not reactive to significantly benefit budgeting and contain disease outbreaks in animal sources before the risk of spillover to human can be envisaged.

Dromedary camels have been implicated consistently as the source of Middle East respiratory syndrome coronavirus (MERS-CoV) human infections and attention to prevent and control it has focused on camels. To understanding the epidemiological role of camels in the transmission of MERS-CoV, we utilized an iterative empirical process in Geographic Information System (GIS) to identify and qualify potential hotspots for maintenance and circulation of MERS-CoV, and produced risk-based surveillance sites in Kenya. Data on camel population and distribution were used to develop camel density map, while camel farming system was defined using multi-factorial criteria including the agro-ecological zones (AEZs), production and marketing practices. Primary and secondary MERS-CoV seroprevalence data from specific sites were analyzed, and location-based prevalence matching with camel densities was conducted. High-risk convergence points (migration zones, trade routes, camel markets, slaughter slabs) were profiled and frequent cross-border camel movement mapped. Results showed that high camel-dense areas and interaction (markets and migration zones) were potential hotspot for transmission and spread. Cross-border contacts occurred with in-migrated herds at hotspot locations. AEZ differential did not influence risk distribution and plausible risk factors for spatial MERS-CoV hotspots were camel densities, previous cases of MERS-CoV, high seroprevalence and points of camel convergences. Although Kenyan camels are predisposed to MERS-CoV, no shedding is documented to date. These potential hotspots, determined using anthropogenic, system and trade characterizations should guide selection of sampling/surveillance sites, high-risk locations, critical areas for interventions and policy development in Kenya, as well as instigate further virological examination of camels. Electronic supplementary material The online version of this article (10.1007/s10393-018-1317-6) contains supplementary material, which is available to authorized users.

Approximately 1500 people die annually due to rabies in the United Republic of Tanzania. Moshi, in the Kilimanjaro Region, reported sporadic cases of human rabies between 2017 and 2018. In response and following a One Health approach, we implemented surveillance, monitoring, as well as a mass vaccinations of domestic pets concurrently in &gt, 150 villages, achieving a 74.5% vaccination coverage (n = 29, 885 dogs and cats) by September 2018. As of April 2019, no single human or animal case has been recorded. We have observed a disparity between awareness and knowledge levels of community members on rabies epidemiology. Self-adherence to protective rabies vaccination in animals was poor due to the challenges of costs and distances to vaccination centers, among others. Incidence of dog bites was high and only a fraction (65%) of dog bite victims (humans) received post-exposure prophylaxis. A high proportion of unvaccinated dogs and cats and the relative intense interactions with wild dog species at interfaces were the risk factors for seropositivity to rabies virus infection in dogs. A percentage of the previously vaccinated dogs remained unimmunized and some unvaccinated dogs were seropositive. Evidence of community engagement and multi-coordinated implementation of One Health in Moshi serves as an example of best practice in tackling zoonotic diseases using multi-level government efforts. The district-level establishment of the One Health rapid response team (OHRRT), implementation of a carefully structured routine vaccination campaign, improved health education, and the implementation of barriers between domestic animals and wildlife at the interfaces are necessary to reduce the burden of rabies in Moshi and communities with similar profiles.

Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an emerging viral disease and dromedary camels are known to be the source of human spill over events. A cross-sectional epidemiological surveillance study was carried out in Kenya in 2017 to, 1) estimate MERS-CoV antibody seropositivity in the camel-dense counties of Turkana, Marsabit, Isiolo, Laikipia and Nakuru to identify, and 2) determine the risk factors associated with seropositivity in camels. Blood samples were collected from a total of 1421 camels selected using a multi-stage sampling method. Data were also collected from camel owners or herders using a pre-tested structured questionnaire. The sera from camel samples were tested for the presence circulating antibodies to MERS-CoV using the anti-MERS-CoV IgG ELISA test. Univariate and multivariable statistical analysis were used to investigate factors potentially associated with MERS-CoV seropositivity in camels. The overall seropositivity in camel sera was 62.9 %, with the highest seropositivity recorded in Isiolo County (77.7 %), and the lowest seropositivity was recorded in Nakuru County (14.0 %). When risk factors for seropositivity were assessed, the “Type of camel production system” {(aOR = 5.40(95 %CI: 1.67–17.49)}, “Age between 1–2 years, 2–3 years and above 3 years” {(aOR = 1.64 (95 %CI: 1.04–2.59}”, {(aOR = 3.27 (95 %CI: 3.66–5.61)}” and {(aOR = 6.12 (95 %CI: 4.04–9.30)} respectively and “Sex of camels” {(aOR = 1.75 (95 %CI: 1.27–2.41)} were identified as significant predictors of MERS-CoV seropositivity. Our studies indicate a high level of seropositivity to MERS-CoV in camels in the counties surveyed, and highlights the important risk factors associated with MERS-CoV seropositivity in camels. Given that MERS-CoV is a zoonosis, and Kenya possesses the fourth largest camel population in Africa, these findings are important to inform the development of efficient and risk-based prevention and mitigation strategies against MERS-CoV transmission to humans.

Dear Editor,MERS-Coronavirus (CoV) is a dromedary-transmitted zoonotic pathogen that is associated with severe viral pneumonia in humans1. As of 28 September 2018, 2249 infections and 798 fatalitie...

A cross-sectional study was conducted in Egypt to determine the prevalence of Middle East respiratory syndrome coronavirus (MERS-CoV) in imported and resident camels and bats, as well as to assess possible transmission of the virus to domestic ruminants and equines. A total of 1,031 sera, 1,078 nasal swabs, 13 rectal swabs, and 38 milk samples were collected from 1,078 camels in different types of sites. In addition, 145 domestic animals and 109 bats were sampled. Overall, of 1,031 serologically-tested camels, 871 (84.5%) had MERS-CoV neutralising antibodies. Seroprevalence was significantly higher in imported (614/692; 88.7%) than resident camels (257/339; 5.8%) (p

Background Highly pathogenic avian influenza (HPAI) viruses of the H5N1 subtype are widely distributed within poultry populations in Egypt and have caused multiple human infections. Linking the epidemiological and sequence data is important to understand the transmission, persistence and evolution of the virus. This work describes the phylogenetic dynamics of H5N1 based on molecular characterization of the hemagglutinin (HA) gene of isolates collected from February 2006 to May 2014. Methods Full-length HA sequences of 368 H5N1 viruses were generated and were genetically analysed to study their genetic evolution. They were collected from different poultry species, production sectors, and geographic locations in Egypt. The Bayesian Markov Chain Monte Carlo (BMCMC) method was applied to estimate the evolutionary rates among different virus clusters; additionally, an analysis of selection pressures in the HA gene was performed using the Single Likelihood Ancestor Counting (SLAC) method. Results The phylogenetic analysis of the H5 gene from 2006–14 indicated the presence of one virus introduction of the classic clade (2.2.1) from which two main subgroups were originated, the variant subgroup which was further subdivided into 2 sub-divisions (2.2.1.1 and 2.2.1.1a) and the endemic subgroup (2.2.1.2). The clade 2.2.1.2 showed a high evolution rate over a period of 6 years (6.9 × 10−3 sub/site/year) in comparison to the 2.2.1.1a variant cluster (7.2 × 10−3 over a period of 4 years). Those two clusters are under positive selection as they possess 5 distinct positively selected sites in the HA gene. The mutations at 120, 154, and 162 HA antigenic sites and the other two mutations (129∆, I151T) that occurred from 2009–14 were found to be stable in the 2.2.1.2 clade. Additionally, 13 groups of H5N1 HPAI viruses were identified based on their amino acid sequences at the cleavage site and “EKRRKKR” became the dominant pattern beginning in 2013. Conclusions Continuous evolution of H5N1 HPAI viruses in Egypt has been observed in all poultry farming and production systems in almost all regions of the country. The wide circulation of the 2.2.1.2 clade carrying triple mutations (120, 129∆, I151T) associated with increased binding affinity to human receptors is an alarming finding of public health importance. Electronic supplementary material The online version of this article (doi:10.1186/s12985-016-0477-7) contains supplementary material, which is available to authorized users.

A distinct cluster of highly pathogenic avian influenza viruses of subtype A(H5N1) has been found to emerge within clade 2.2.1.2 in poultry in Egypt since summer 2014 and appears to have quickly become predominant. Viruses of this cluster may be associated with increased incidence of human influenza A(H5N1) infections in Egypt over the last months.

Many developing countries lack sufficient resources to conduct animal disease surveillance. In recent years, participatory epidemiology has been used to increase the cover and decrease the costs of surveillance. However, few diagnostic performance assessments have been carried out on participatory methods. The objective of the present study was to estimate the diagnostic performance of practitioners working for the Community-Based Animal Health and Outreach (CAHO) program, which is a participatory disease surveillance system for the detection of highly pathogenic avian influenza outbreaks in Egypt. CAHO practitioners' diagnostic assessment of inspected birds was compared with real-time reverse-transcriptase polymerase chain reaction (RRT-PCR) test results at the household level. Diagnostic performance was estimated directly from two-by-two tables using RRT-PCR as a reference test in two different scenarios. In the first scenario, only results from chickens were considered. In the second scenario, results for all poultry species were analyzed. Poultry flocks in 916 households located in 717 villages were inspected by CAHO practitioners, who collected 3458 bird samples. In the first scenario, CAHO practitioners presented sensitivity (Se) and specificity (Sp) estimates of 40% (95% confidence interval [CI]: 21%-59%) and 92% (95% CI: 91%-94%), respectively. In the second scenario, diagnostic performance estimates were Se = 47% (95% CI: 29%-65%) and Sp = 88% (95% CI: 86%-90%). A significant difference was observed only between Sp estimates (P0.01). Practitioners' diagnostics and RRT-PCR results were in very poor agreement with kappa values of 0.16 and 0.14 for scenarios 1 and 2, respectively. However, the use of a broad case definition, the possible presence of immunity against the virus in replacement birds, and the low prevalence observed during the survey would negatively affect the practitioners' performance.

Vaccination of domestic poultry against avian influenza (AI) has been used on a large-scale in South East Asia since 2003 and in Egypt since 2006 to fight H5N1 highly-pathogenic avian influenza (HPAI) epidemics. The decision to use mass vaccination against HPAI in Egypt was taken as an emergency measure based on positive impact of such control measures in Vietnam and the People's Republic of China. However, three years on, the impact on disease control of AI vaccination in Egypt has been very limited. Despite the continuous vaccination of poultry against HPAI, poultry outbreaks and human cases are reported regularly. A recent assessment study highlighted substantial weaknesses in the current immunisation programme and its lack of positive impact on the spread of infection or the maintenance of public health safety. The shortcomings of the vaccination strategy may be attributed in part to a lack of sufficient support in terms of funding and communication, the absence of an efficient monitoring system, and inadequate training of field technicians. The difficulties of blanket vaccinations in semi-commercial farms and household poultry sectors are well known, however, improvements in the industrial sector should be possible though better government controls and greater collaboration with the private sector. AI vaccination should be regarded as just one control tool within a broader disease control program integrating surveillance, outbreak investigation, disease management systems, and the rigorous implementation of bio-security measures. If incorrectly implemented, AI vaccination has a limited impact as a disease control measure. Moreover, without strict bio-security precautions undertaken during its application, farm visits to vaccinate poultry could facilitate the spread of the virus and therefore become a risk factor with important implications on the maintenance of the virus and potential risk for human exposure.

Background Influenza A H5N1 has killed millions of birds and raises serious public health concern because of its potential to spread to humans and cause a global pandemic. While the early focus was in Asia, recent evidence suggests that Egypt is a new epicenter for the disease. This includes characterization of a variant clade 2.2.1.1, which has been found almost exclusively in Egypt. We analyzed 226 HA and 92 NA sequences with an emphasis on the H5N1 2.2.1.1 strains in Egypt using a Bayesian discrete phylogeography approach. This allowed modeling of virus dispersion between Egyptian governorates including the most likely origin. Results Phylogeography models of hemagglutinin (HA) and neuraminidase (NA) suggest Ash Sharqiyah as the origin of virus spread, however the support is weak based on Kullback–Leibler values of 0.09 for HA and 0.01 for NA. Association Index (AI) values and Parsimony Scores (PS) were significant (p-value