Spatial clustering of swine influenza in Ontario on the basis of herd-level disease status with different misclassification errors

Does Vaccine-Induced Maternally-Derived Immunity Protect Swine Offspring against Influenza a Viruses? A Systematic Review and Meta-Analysis of Challenge Trials from 1990 to May 2021

It is unclear if piglets benefit from vaccination of sows against influenza. For the first time, methods of evidence-based medicine were applied to answer the question: "Does vaccine-induced maternally-derived immunity (MDI) protect swine offspring against influenza A viruses?". Challenge trials were reviewed that were published from 1990 to April 2021 and measured at least one of six outcomes in MDI-positive versus MDI-negative offspring (hemagglutination inhibition (HI) titers, virus titers, time to begin and time to stop shedding, risk of infection, average daily gain (ADG), and coughing) (n = 15). Screening and extraction of study characteristics was conducted in duplicate by two reviewers, with data extraction and assessment for risk of bias performed by one. Homology was defined by the antigenic match of vaccine and challenge virus hemagglutinin epitopes. Results: Homologous, but not heterologous MDI, reduced virus titers in piglets. There was no difference, calculated as relative risks (RR), in infection incidence risk over the entire study period; however, infection hazard (instantaneous risk) was decreased in pigs with MDI (log HR = -0.64, 95% CI: -1.13, -0.15). Overall, pigs with MDI took about a ½ day longer to begin shedding virus post-challenge (MD = 0.51, 95% CI: 0.03, 0.99) but the hazard of infected pigs ceasing to shed was not different (log HR = 0.32, 95% CI: -0.29, 0.93). HI titers were synthesized qualitatively and although data on ADG and coughing was extracted, details were insufficient for conducting meta-analyses. Conclusion: Homology of vaccine strains with challenge viruses is an important consideration when assessing vaccine effectiveness. Herd viral dynamics are complex and may include concurrent or sequential exposures in the field. The practical significance of reduced weaned pig virus titers is, therefore, not known and evidence from challenge trials is insufficient to make inferences on the effects of MDI on incidence risk, time to begin or to cease shedding virus, coughing, and ADG. The applicability of evidence from single-strain challenge trials to field practices is limited. Despite the synthesis of six outcomes, challenge trial evidence does not support or refute vaccination of sows against influenza to protect piglets. Additional research is needed; controlled trials with multi-strain concurrent or sequential heterologous challenges have not been conducted, and sequential homologous exposure trials were rare. Consensus is also warranted on (1) the selection of core outcomes, (2) the sizing of trial populations to be reflective of field populations, (3) the reporting of antigenic characterization of vaccines, challenge viruses, and sow exposure history, and (4) on the collection of non-aggregated individual pig data.

Active regional surveillance for early detection of exotic/emerging pathogens of swine: A comparison of statistical methods for farm selection

In this study, five spatially balanced sampling methods, i.e., generalized random-tessellation stratified (GRTS), local pivotal method (LPM), spatially correlated Poisson sampling (SCPS), local cube method (LCUBE), and balanced acceptance sampling (BAS) were compared to simple random sampling (SRS) based on a livestock disease transmission model on a hypothetical region (195 km × 300 km) populated with 6000 farms in terms of the probability of detection by sample size. Given a fixed sample size, four of the five spatially balanced sampling methods provided better performance than SRS, i.e., higher probabilities of detecting at least one infected farms over a range of regional prevalence evaluated (1%-5%). That is, for any given probability of detection, spatially balanced methods required testing fewer farms than SRS. In an era of pandemics, active regional surveillance for early detection of emerging pathogens becomes urgent, yet shrinking budgets impose intractable constraints. The better performance and higher efficiency of spatially balanced sampling methods suggests a potential improvement in regional livestock disease surveillances and a partial solution to the challenge of affordable surveillance.

Breed-to-wean farm factors associated with influenza A virus infection in piglets at weaning

Breed-to-wean pig farms play an important role in spreading influenza A virus (IAV) because suckling piglets maintain, diversify and transmit IAV at weaning to other farms. Understanding the nature and extent of which farm factors drive IAV infection in piglets is a prerequisite to reduce the burden of influenza in swine. We evaluated the association between IAV infection in piglets at weaning and farm factors including farm features, herd management practices and gilt- and piglet-specific management procedures performed at the farm. Voluntarily enrolled breed-to-wean farms (n = 83) agreed to share IAV diagnostic testing and farm data from July 2011 through March 2017 including data obtained via the administration of a survey. There were 23% IAV RT-PCR positive samples of the 12,814 samples submitted for IAV testing within 2989 diagnostic submissions with 30% positive submissions. Among all the factors evaluated (n = 24), and considering the season-adjusted multivariable analysis, only sow IAV vaccination and gilt IAV status at entry significantly reduced (p-value<0.05) IAV infections in piglets at weaning. Results from this study indicate that veterinarians and producers could manage these identified factors to reduce the burden of influenza in piglets prior to wean and perhaps, reduce the spread of IAV to other farms and people.

Molecular detection of influenza A(H1N1)pdm09 viruses with M genes from human pandemic strains among Nigerian pigs, 2013-2015: implications and associated risk factors

In the post-pandemic period, influenza A(H1N1)pdm09 virus has been detected in swine populations in different parts of the world. This study was conducted to determine the presence and spatial patterns of this human pandemic virus among Nigerian pigs and identify associated risk factors. Using a two-stage stratified random sampling method, nasal swab specimens were obtained from pigs in Ibadan, Nigeria during the 2013-2014 and 2014-2015 influenza seasons, and the virus was detected by reverse transcriptase-polymerase chain reaction (RT-PCR). Purified RT-PCR products were sequenced in both directions, and sequences were aligned using MUSCLE. Phylogenetic analysis was conducted in MEGA6. Purely spatial scan statistics and a spatial lag regression model were used to identify spatial clusters and associated risk factors. The virus was detected in both seasons, with an overall prevalence of 8·7%. Phylogenetic analyses revealed that the M genes were similar to those of pandemic strains which circulated in humans prior to and during the study. Cluster analysis revealed a significant primary spatial cluster (RR = 4·71, LLR = 5·66, P = 0·0046), while 'hours spent with pigs (R 2 = 0·90, P = 0·0018)' and 'hours spent with pigs from different farms (R 2 = 0·91, P = 0·0001)' were identified as significant risk factors (P < 0·05). These findings reveal that there is considerable risk of transmission of the pandemic virus, either directly from pig handlers or through fomites, to swine herds in Ibadan, Nigeria. Active circulation of the virus among Nigerian pigs could enhance its reassortment with endemic swine influenza viruses. Campaigns for adoption of biosecurity measures in West African piggeries and abattoirs should be introduced and sustained in order to prevent the emergence of a new influenza epicentre in the sub-region.

Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems

During the last 30years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively.

The use of epidemiology to enhance production animal research

The approach to understanding the impact of management and disease in production animal systems has evolved with the advent of both routine on-farm data collection and new analytic epidemiology techniques. Epidemiology provides a tool to describe the host-agent-environment triad and the impact of multiple variables on productivity and health recognized by production animal veterinarians in their day-to-day work. Field trials enable veterinarians to systematically test whether or not a new treatment improves the health of the animal populations in their geographic region and under their production systems. Hypothesis-specific coding techniques, such as hierarchical variables, are used in a systematic manner to understand well-defined biological phenomenon. Clustering at multiple levels has provided the challenges of measuring management changes in each level. Using random effects models allow us to determine the relative importance of each level on the dependent variable. As epidemiologists, we have taken advantage of analytic techniques used in other fields of science. Geo-spatial statistics has been used to understand the clustering and spread of diseases and more recently, to interpret the laboratory findings related to the introduction of an exotic strain of the influenza virus. Dr. Martin, through his work as a veterinary epidemiologist and that of people he has influenced, has been an international leader in promoting the optimal health and productivity of animal populations and of ensuring the safety of foods of animal origin and preventing animal-related disease in humans.

Investigation of exposure to swine influenza viruses in Ontario (Canada) finisher herds in 2004 and 2005

The epidemiology of influenza in the North American swine population has changed since the emergence of a triple-reassortant H3N2 influenza virus. Although seen previously in North America, the Ontario swine population had likely been free of viruses of the reassortant H3N2 lineage until 2005. The objective of this study was to investigate the frequency and distribution of exposure to H1N1 and H3N2 subtypes in the Ontario finisher pig population prior to and after the H3N2 outbreak that occurred in 2005. This included investigating prevalence and spatial distribution of positive herds, assessing proportion of random variation at different hierarchical levels, and evaluating selected demographic factors and management procedures as potential risk factors. In total, 919 and 978 sera collected in cross-sectional studies from 46 and 49 finisher herds in 2004 and 2005 were tested by a H1N1 subtype-specific and a H3N2 subtype-specific commercial ELISA. For the H1N1 subtype, the point prevalence of positive herds (>3 reactors) was 19.5% and 30.6% in 2004 and 2005, respectively. For the H3N2 subtype the point prevalence of positive herds (>3 reactors) was 6.5% and 40.8% in 2004 and 2005, respectively. Sera from 2004 that were positive on H3N2 ELISA did not cross-react with any of the H3N2 variants used as antigen on a sequential HI test. Only herds positive for H3N2 subtype in 2005 clustered in space (P<0.01). The H1N1 status in 2005 was associated with the H1N1 status in 2004, and with reported distance to the nearest herd. The H3N2 status in 2005 was associated with reported distance to the nearest herd and a type of replacement gilt source. For H3N2, distance seemed to be important even after controlling for type of gilt source. Most variability in seropositivity was between herds with little variability between pens. This study confirms that in 2005, the epidemic H3N2 subtype co-circulated with endemic H1N1 subtype in the Ontario finisher herds. We concluded that in Ontario, the endemic H1N1 subtype was likely maintained through circulation within herds and sites with common flow. Whereas the transmission of epidemic H3N2 subtype was attributed to local spread, which could include different modes of direct, indirect, and airborne transmission. We emphasize the importance of establishing routine monitoring systems that would allow using molecular tools, and maintaining serum banks as a useful resource for retrospective comparisons.