Risk-based Surveillance Systems Research Articles

Systematic literature review: Assessing community health hazards arising from food safety concerns in the food market

Food safety concerns have an immediate impact on public health. The food market is an important node for investigating possible risks due to its central role in the delivery of food goods to communities. Health concerns are internationalized as food supply chains span many countries. Therefore, we undertook this literature study to uncover widespread threats to public health from inadequate food safety measures. The online databases were examined for any quantitative, qualitative or mixed-method studies that had been published and they were in the process of publishing. Prisma table analysis was used to determine the level of methodological quality in the included research. Using a qualitative analysis strategy, we classified the ideas in the full-text articles into overarching categories that share commonalities but are not mutually exclusive. After identifying commonalities in the articles' discussions and final thoughts, we synthesized each subject. After a thorough and methodical reading, recurring motifs were uncovered. During analysis, we got better at categorizing and analyzing the data. The examination of 7 full-text papers resulted in common public health issues linked with food safety in the food industry. The expiration dates on these products were demonstrated to pose a serious risk to healthcare in the food sector. The food industry faces several public health issues discovered in this evaluation of the relevant research. As a result, robust national risk-based food surveillance systems are necessary to guarantee the public's safety. Foods entering global trade must be guaranteed to be safe and of high quality as well as imported foods must meet domestic standards. Regulatory bodies, players in the food sector and consumers need to work together to find effective solutions to these problems. By addressing these issues, we can work toward making the food market a place where everyone can feel secure and healthy.

Modeling transmission of avian influenza viruses at the human-animal-environment interface in Cuba.

The increasing geographical spread of highly pathogenic avian influenza viruses (HPAIVs) is of global concern due to the underlying zoonotic and pandemic potential of the virus and its economic impact. An integrated One Health model was developed to estimate the likelihood of Avian Influenza (AI) introduction and transmission in Cuba, which will help inform and strengthen risk-based surveillance activities. The spatial resolution used for the model was the smallest administrative district ("Consejo Popular"). The model was parameterised for transmission from wild birds to poultry and pigs (commercial and backyard) and then to humans. The model includes parameters such as risk factors for the introduction and transmission of AI into Cuba, animal and human population densities; contact intensity and a transmission parameter (β). Areas with a higher risk of AI transmission were identified for each species and type of production system. Some variability was observed in the distribution of areas estimated to have a higher probability of AI introduction and transmission. In particular, the south-western and eastern regions of Cuba were highlighted as areas with the highest risk of transmission. These results are potentially useful for refining existing criteria for the selection of farms for active surveillance, which could improve the ability to detect positive cases. The model results could contribute to the design of an integrated One Health risk-based surveillance system for AI in Cuba. In addition, the model identified geographical regions of particular importance where resources could be targeted to strengthen biosecurity and early warning surveillance.

Evaluation of diagnostic tests’ sensitivity, specificity and predictive values in bovine carcasses showing brucellosis suggestive lesions, condemned by Brazilian Federal Meat Inspection Service in the Amazon Region of Brazil

Cervical bursitis is a suggestive lesion of bovine brucellosis. Diagnostic sensitivity and specificity of two brucellosis serological tests, Rose Bengal (RB) and serum agglutination test with 2-mercaptoethanol (SAT/2-ME), and of isolation and identification (bacteriology) were evaluated through Bayesian latent class analysis (BLCA). A total of 165 paired serum and cervical bursitis samples detected at inspection by Brazilian federal meat inspection services were analyzed. The best model fit to the data occurred when accounting for the conditional dependence between serological tests. According to this model, RB and SAT/2-ME had almost the same sensitivity, 0.960 [0.903 – 0.992] and 0.963 [0.906 – 0.994] with 95 % Credible Interval (95 %CrI), respectively. Specificities were 0.9068 [0.562 – 0.997] and 0.875 [0.546 – 0.990] for RB and SAT/2-ME, respectively, also with 95 %CrI. Bacteriology had lower sensitivity than serological tests, 0.594 (95 %CrI: [0.525 – 0.794]) and the highest specificity of all evaluated tests, 0.992 (95 %CrI: [0.961–1.00]). Prevalence of infected animals was 0.829 (95 %CrI: [0.700−0.900]). BLCA showed that both RB and SAT/2-ME fitted to the purpose of initial screening the brucellosis suspect in carcasses with cervical bursitis in a reliable way. The results of RB or SAT/2-ME can guide the sanitary actions for brucellosis control and help the implementation of a risk-based surveillance system in the meat production chain. This strategy is especially true in remote areas with large beef cattle herds, raised extensively, where in vivo tests are rarely performed due to logistic and management constraints, as in the Northern region of Brazil.

Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds.

Highly pathogenic avian influenza (HPAI) has predominantly damaged the poultry industry worldwide. The fundamental prevention and control strategy for HPAI includes early detection and timely intervention enforcement through a systematic surveillance system for wild birds based on the ecological understanding of the dynamics of wild birds' movements. Our study aimed to develop a spatiotemporal risk assessment model for avian influenza (AI) infection in wild birds to empower surveillance information for a contingency strategy. For this purpose, first, we predicted the monthly habitat suitability of seven waterfowl species, using 227,671 Global Positioning System (GPS) tracking records of 562 birds from 2014 to 2018 in the Republic of Korea (ROK). Then, that predicted habitat suitability and 421 coordinates of AI detection sites in wild birds were used to build the risk assessment model. Subsequently, we compared the monthly predicted risk of avian influenza virus (AIv) identification in wild birds between case and non-case poultry farms with HPAI H5N6 outbreak in the ROK between 2016 and 2017. The results reported considerable variation of monthly habitat suitability of seven waterfowls and the impact of predicting AI occurrences in wild birds. The high habitat suitability for spot-billed ducks (contribution rate in November=40.9%) and mallards (contribution rate in January=34.3%) significantly contributed to predicting the average risk of AIv identification in wild birds, with high predictive performance [the monthly mean of area under the curve (AUC)=0.978]. Moreover, our model showed that the averaged risk of identification AI in wild birds was significantly higher in HPAI infected premises, with infected domestic duck holdings exhibiting a significantly higher risk than the chicken farms in November. This study suggests that animal health authority establishes a risk-based HPAI surveillance system grounded on the ecological nature of wild birds to improve the effectiveness of prevention and preparedness of emerging epidemics.

Substandard and Falsified Medicines: Proposed Methods for Case Finding and Sentinel Surveillance.

The World Health Organization and others warn that substandard and falsified medicines harm health and waste money, especially in low- and middle-income countries. However, no country has measured the market-wide extent of the problem, and no standardized methods exist to estimate the prevalence of either substandard or falsified medicines. This is, in part, because the task seems overwhelming; medicine markets are huge and diverse, and testing medicines is expensive. Many countries do operate some form of postmarket surveillance of medicine, but their methods and goals differ. There is currently no clear guidance on which surveillance method is most appropriate to meet specific public health goals. In this viewpoint, we aimed to discuss the utility of both case finding and risk-based sentinel surveillance for substandard and falsified medicines, linking each to specific public health goals. We posit that choosing the system most appropriate to the goal, as well as implementing it with a clear understanding of the factors driving the production and sale of substandard and falsified medicines, will allow for surveillance resources to be concentrated most efficiently. We adapted principles used for disease outbreak responses to suggest a case-finding system that uses secondary data to flag poor-quality medicines, proposing risk-based indicators that differ for substandard and falsified medicines. This system potentially offers a cost-effective way of identifying “cases” for market withdrawal, enhanced oversight, or another immediate response. We further proposed a risk-based sentinel surveillance system that concentrates resources on measuring the prevalence of substandard and falsified medicines in the risk clusters where they are most likely to be found. The sentinel surveillance system provides base data for a transparent, spreadsheet-based model for estimating the national prevalence of substandard and falsified medicines. The methods we proposed are based on ongoing work in Indonesia, a large and diverse middle-income country currently aiming to achieve universal health coverage. Both the case finding and the sentinel surveillance system are designed to be adaptable to other resource-constrained settings.

Shiga Toxin–Producing Escherichia coli Contamination of Raw Beef and Beef-Based Ready-to-Eat Products at Retail Outlets in Pretoria, South Africa

A cross-sectional study was conducted to determine the prevalence of and factors associated with Shiga toxin-producing Escherichia coli (STEC) in raw beef and ready-to-eat (RTE) beef products sold in 31 retail outlets in Pretoria, South Africa, and nearby areas. A total of 463 beef and RTE samples were screened for four STEC virulence genes (stx1, stx2, eaeA, and hlyA) and seven O-serogroups (O113, O157, O26, O91, O145, O111, and O103) with a multiplex PCR assay. The total aerobic plate count (TAPC) per gram was also determined. A total of 38 STEC isolates were recovered and characterized by conventional PCR assay and serotyping. The overall prevalence of STEC in the beef and RTE samples tested was 16.4% (76 of 463 samples; 95% confidence interval, 13 to 20%). The prevalence of STEC differed significantly by product type (P < 0.0001), with the highest prevalence (35%) detected in boerewors (spicy sausage). The STEC prevalences in minced beef, brisket, RTE cold beef, and biltong were 18, 13, 9, and 5%, respectively. The most frequently detected stx gene was stx2 (13%), and STEC serogroups from recovered isolates were detected at the following prevalences: O2, 15%; O8, 12%; O13, 15%; O20, 8%; O24, 3%; O39, 3%; O41, 8%; O71, 3%; O76, 3%; O150, 12%; and O174, 3%. A high proportion (77%) of the samples had TAPCs that exceeded the South African microbiological standards for meat export (5.0 log CFU/g). The prevalence of O157 STEC (16%) and the diversity of non-O157 STEC serogroups found in five common beef-based products from retail outlets in South Africa suggest exposure of raw beef and beef products to multiple contamination sources during carcass processing and/or cutting and handling at retail outlets. These data provide direct estimates of the potential health risk to consumers from undercooked contaminated products and indicate the need to improve sanitary practices during slaughter and processing of beef and beef-based RTE products. A risk-based surveillance system for STEC may be needed.

Epidemiological Situation of Schigеllosis in the Republic of Dagestan and Directions for Improving Epidemiological Surveillance

Relevance.Acute intestinal infections still retain their social and medical significance in the world, with a reduction in the incidence of well-studied bacterial infections, such as salmonellosis and, especially, shigellosis.Discussion.Since 2006, the incidence of bacterial dysentery in Russia has continued to decrease, in the Republic of Dagestan it is at a high level, exceeding more than 10 times the national average. Mostly children are sick (up to 75%). Cases of shigellosis are recorded throughout the year, the seasonal increase in the incidence in the summer and autumn is associated with the activity of the main transmission pathogens – water and food. The main causes of epidemiological well-being for schigеllosis in Dagestan are determined by: poor state of the water supply system and sanitary and communal improvement of populated areas; the use of food products stored, transported and sold in the distribution network in violation of sanitary and hygienic requirements. So, in 2017 and 2018 – 67.1% and 32.69% of drinking water samples of water pipelines did not meet hygienic standards, respectively, in terms of sanitary and chemical indicators, 53.1% and 65.6% of water pipelines did not meet the requirements of sanitary legislation. The flare incidence, which is recorded annually, indicates the activity of the epidemic process of acute intestinal infections and shigellosis in the republic. The experience of various territories of the country, including those affected by adverse environmental and climatic phenomena (floods, floods, flooding), shows high efficiency along with traditional measures aimed at breaking the transmission mechanism of the pathogen, Shigellosis vaccine prophylaxis. In Dagestan, vaccination is limited, mainly in foci, where bacteriophage polyvalent dysentery S. sonnei and S. flexneri 1, 2, 3, 4, and 6 serotypes are used more widely for prevention and treatment. In this situation, the optimization of the system of epidemiological surveillance of shigellosis, which consists in improving the pre-epidemic diagnosis and epidemiological monitoring of measures aimed at each link in the epidemic process, including the creation of immunity to pathogens in individual population groups due to specific prevention, is of particular relevance to the Republic.Conclusion.The constant flare incidence of dysentery dictates the need, along with traditional measures to interrupt the transmission of the pathogen, to carry out vaccine prophylaxis more widely in risk groups. Potential sources of shigella have formed in the republic; there is a potentially high risk of the mechanism of transmission of the pathogen, as well as the population potentially susceptible to the pathogen, indicating the presence of such a danger and the need for its comprehensive study as an object of risk-oriented surveillance. Thus, the key directions in improving the surveillance of shigеllosis in the Dagestan Republic should be pre-epidemic diagnosis in a risk-based epidemiological surveillance system. The introduction of modern sensitive, specific, standardized methods of laboratory diagnostics will make it possible to effectively carry out risk-oriented epidemiological surveillance, which makes it possible to identify the transition of risk factors from potential to real, activating the epidemic process.

Optimising the seasonal deployment of surveillance traps for detection of incipient pest invasions

Early detection of biological invasions is necessary to enable successful management responses, such as containment and eradication. Several nations operate risk-based surveillance systems for early detection and proof of freedom from economically damaging pests and diseases. Identifying the best times of year to deploy and remove surveillance traps is important for maximising the probability of detection while minimising the economic costs of large-scale trapping.We modelled seasonal population dynamics to identify which days of the year contribute most to surveillance sensitivity and therefore the appropriate trapping period, and applied this to trapping for fruit flies (Diptera: Tephritidae) in New Zealand. Optimum trapping periods were defined as the minimum contiguous dates which would give a specific proportion (80%, 90%, 95%, or 99%) of the probability of detection compared to year-round trapping. Seasonal dynamics were based on an empirical model for the effect of temperature on population increase and decline, fitted to published data from around the world. The model suggested Mediterranean fruit fly (Medfly) should be trapped in the upper half of the North Island from at least November through May. Additional trapping in October and June may be warranted in the far north. Favourable microclimates or climate change to 2040 may allow Medfly populations to establish as far south as Christchurch and Alexandra, where trapping should run from mid December to early May. Queensland fruit fly (Qfly) and oriental fruit fly were unlikely to establish south of Napier and optimum trapping times for these species are approximately mid November through May. Climate change under moderate scenarios is unlikely to significantly alter the optimum trapping periods until at least 2040.The results were not sensitive to assumptions about trap efficacy and founder population size. However, they are based on simplified relationships between the intrinsic rate of increase and temperature. This approach is applicable to any invasive species with seasonal variation in surveillance efficacy. In response to this work, New Zealand's biosecurity authority has changed the seasonal timing of their fruit fly trapping to optimise detection efficacy.

Prevalence of and environmental factors associated with aerosolised Aspergillus spores at a zoological park

Aspergillus is a significant pathogen in zoological species, although information on environmental variables influencing fungal prevalence in zoological settings are lacking. The objective of the study was to estimate the...

Pseudorabies virus in North-West Italian wild boar (Sus scrofa) populations: prevalence and risk factors to support a territorial risk-based surveillance.

Although the eradication of Pseudorabies virus (PrV) in domestic pigs is ongoing, the circulation of this virus in wild boars remains a threat in the currently unprotected, 'low prevalence', pig population. In this study, we reported PrV prevalence data and the influence of possible risk factors in 2 North-West Italian wild boar populations (free and enclosed) with the goal of supporting the implementation of a risk-based AD surveillance system. Sera from 1,425 wild boars were collected between 2011 and 2015 and tested by ELISA for the presence of PrV antibodies; the overall raw seroprevalence was 30.39% (433/1,425; CI 95% 28.01-32.85%). A significant difference was however observed between the prevalence rates of the free range population (9.98%; 90/902; CI 95%; 8.10-12.12%) and the enclosed population of La Mandria park (Piedmont, Italy) (65.58%; 343/523; CI 95%; 61.51-69.65%). In both populations a significantly higher number of adults and females were found positive to PrV ELISA. Specific territorial data on PrV circulation in wild boars should be acquired from other regions for guiding risk-based measures in order to reduce the threat of AD re-infection in a more cost-effective manner.

Biosecurity system reforms and the development of a risk-based surveillance and pathway analysis system for ornamental fish imported into Australia

The ornamental fish trade in Australia has an estimated value of AUD$350 million and involves importation of up to 20 million fish from 26 approved countries each year. Critical reviews indicated that the biosecurity system did not fully manage the risks associated with fish that were sub-clinically infected with diseases such as megalocytiviruses, or the threats posed by emerging diseases. Subsequent reforms have placed a greater emphasis on managing biosecurity risks off-shore at the source, coupled with an on-arrival surveillance system to assess compliance with biosecurity regulation.This presentation at the first global Conference in Aquatic Animal Epidemiology in Oslo, Norway in September 2016, describes the Department of Agriculture Water Resources’ current initiatives to address increased risks in real-time while facilitating safe trade. The department is developing an innovative real-time, responsive risk-based surveillance capability to detect systemic failures on the part of the animal health authorities.The program involves a risk-based sampling algorithm on ornamental fish imported into Australia and testing for megalocytiviruses, spring viraemia of carp virus and Aeromonas salmonicida.We present the system and the results from several trials. The information generated by the verification surveillance system will be quantitative and semi-quantitative in nature and will form the basis of the department’s response to detect systematic non-compliances by overseas authorities. Evidence collected through the ongoing analysis of surveillance data will become the basis of real-time feedback to overseas authorities for remedial action at source. Delays in resolving non-compliance issues could result in the suspension of off-shore equivalent measures from particular sources.

Livestock trade network: potential for disease transmission and implications for risk-based surveillance on the island of Mayotte

The island of Mayotte is a department of France, an outermost region of the European Union located in the Indian Ocean between Madagascar and the coast of Eastern Africa. Due to its close connection to the African mainland and neighbouring islands, the island is under constant threat of introduction of infectious diseases of both human and animal origin. Here, using social network analysis and mathematical modelling, we assessed potential implications of livestock movements between communes in Mayotte for risk-based surveillance. Our analyses showed that communes in the central region of Mayotte acted as a hub in the livestock movement network. The majority of livestock movements occurred between communes in the central region and from communes in the central region to those in the outer region. Also, communes in the central region were more likely to be infected earlier than those in the outer region when the spread of an exotic infectious disease was simulated on the livestock movement network. The findings of this study, therefore, suggest that communes in the central region would play a major role in the spread of infectious diseases via livestock movements, which needs to be considered in the design of risk-based surveillance systems in Mayotte.

MOVEMENTS OF LIVE SALMONIDS IN SCOTLAND: CONSERVATION OF NETWORK STRUCTURE

MOVEMENTS OF LIVE SALMONIDS IN SCOTLAND: CONSERVATION OF NETWORK STRUCTURE

Biosecurity system reforms and the development of a risk-based surveillance and pathway analysis system for ornamental fish imported into Australia

Biosecurity system reforms and the development of a risk-based surveillance and pathway analysis system for ornamental fish imported into Australia

Risk-based surveillance and pathway analysis system for aquatic animals for international trade purposes

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Mapping as a tool for predicting the risk of anthrax outbreaks in Northern Region of Ghana.

IntroductionAnthrax is a febrile soil-born infectious disease that can affect all warm-blooded animals including man. Outbreaks of anthrax have been reported in northern region of Ghana but no concerted effort has been made to implement risk-based surveillance systems to document outbreaks so as to implement policies to address the disease. We generated predictive maps using soil pH, temperature and rainfall as predictor variables to identify hotspot areas for the outbreaks.MethodsA 10-year secondary data records on soil pH, temperature and rainfall were used to create climate-based risk maps using ArcGIS 10.2. The monthly mean values of rainfall and temperature for ten years were calculated and anthrax related evidence based constant raster values were created as weights for the three factors. All maps were generated using the Kriging interpolation method.ResultsThere were 43 confirmed outbreaks. The deaths involved were 131 cattle, 44 sheep, 15 goats, 562 pigs with 6 human deaths and 22 developed cutaneous anthrax. We found three strata of well delineated distribution pattern indicating levels of risk due to suitability of area for anthrax spore survival. The likelihood of outbreaks occurrence and reoccurrence was higher in Strata I, Strata II and strata III respectively in descending order, due to the suitability of soil pH, temperature and rainfall for the survival and dispersal of B. anthracis spore.ConclusionThe eastern corridor of Northern region is a Hots spot area. Policy makers can develop risk based surveillance system and focus on this area to mitigate anthrax outbreaks and reoccurrence.

Design and prospective evaluation of a risk-based surveillance system for shrimp grow-out farms in northeast Brazil

The farming of Pacific white shrimp Litopennaeus vannamei in northeast Brazil, has proven to be a promising sector. However, the farming of Pacific white shrimp in Brazil has been affected negatively by the occurrence of viral diseases, threatening this sector's expansion and sustainability. For this reason, the drafting of a surveillance system for early detection and definition of freedom from viral diseases, whose occurrence could result in high economic loses, is of the utmost importance. The stochastic model AquaVigil was implemented to prospectively evaluate different surveillance strategies to determine freedom from disease and identify the strategy with the lowest sampling efforts, making the best use of available resources through risk-based surveillance. The worked example presented was designed for regional application for the state of Ceará and can easily be applied to other Brazilian states. The AquaVigil model can analyse any risk-based surveillance system that considers a similar outline to the strategy here presented.

Spatiotemporal trends in the discovery of new swine infectious agents

A literature review was conducted to assess the spatiotemporal trend and diversity of infectious agents that were newly found in pigs between 1985 and 2010. We identified 173 new variants from 91 species, of which 73 species had not been previously described in pigs. These new species, of which one third was zoonotic, were taxonomically diverse. They were identified throughout the study period, predominantly in the main pork producing countries, with the rate of discovery of new virus variants doubling within the last 10 years of the study period. Whilst infectious agent species newly detected in high-income countries were more likely to be associated with higher virulence, zoonotic agents prevailed in low- and middle-income countries. Although this trend is influenced by factors conditioning infectious agent detection – diagnostic methods, surveillance efforts, research interests –, it may suggest that different scales and types of production systems promote emergence of certain types of infectious agents. Considering the rapid transformation of the swine industry, concerted efforts are needed for improving our understanding of the factors influencing the emergence of infectious agents. This information then needs to inform the design of risk-based surveillance systems and strategies directly mitigating the risk associated with these factors.Electronic supplementary materialThe online version of this article (doi:10.1186/s13567-015-0226-8) contains supplementary material, which is available to authorized users.

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland.

BackgroundThis study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway.MethodsA framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013.ResultsA cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99 %, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey.ConclusionsThe seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.

Highly pathogenic H7N7 avian influenza in Italy

Since 1997, there have been several occurrences of low pathogenicity avian influenza (LPAI) H5 and H7 viruses in Italy. Furthermore, H5N2 and H7N1 highly pathogenic (HP) AI viruses were responsible...