Evaluation of the impact of live pig trade network, vaccination coverage and socio-economic factors in the classical swine fever eradication program in Peru.

Classical swine fever (CSF) is a viral infectious disease of swine with significant economic impact in the affected countries due to the limitation of trade, culling of infected animals and production losses. In Latin America, CSF is endemic in several countries including Ecuador, Bolivia, Brazil and Peru. Since 2010, the National Veterinary Services of Peru have been working to better control and eradicate the disease with an intensive vaccination program. The aim of this study was to evaluate the effectiveness of the vaccination program and determine which factors are still contributing to the persistence of the disease in certain regions of Peru. We integrated the data from the vaccination campaign, the live pig movement network and other socioeconomic indicators into a multilevel logistic regression model to evaluate their association with CSF occurrence at district level. The results revealed that high vaccination coverage significantly reduces the risk of CSF occurrence (OR = 0.07), supporting the effectiveness of the vaccination program. Districts belonging to large and medium pig trade network communities (as identified with walktrap algorithm) had higher probability to CSF occurrence (OR = 2.83 and OR = 5.83, respectively). The human development index (HDI) and the presence of a slaughterhouse in the district was also significantly associated with an increased likelihood of CSF occurrence (OR = 1.52 and OR = 3.25, respectively). Districts receiving a high proportion of the movements from districts that were infected in the previous year were also at higher risk of CSF occurrence (OR = 3.30). These results should be useful to guide the prioritization of vaccination strategies and may help to design other intervention strategies (e.g., target education, movement restrictions, etc.) in high-risk areas to more rapidly advance in the eradication of CSF in Peru.

Behaviour of Quercus pollen in the air, determination of its sources and transport through the atmosphere of Mexico City and conurbated areas.

Pollen allergies have a remarkable clinical impact all over world. Quercus pollen is the main allergen in many parts of world. Due to the health impacts caused by exposure to oak pollen, the objectives of this study are to characterise the aerobiological behaviour of Quercus pollen and to determine its potential sources as well as their transport through the atmosphere of Mexico City and surrounding areas between January 2012 and June 2015. Airborne Quercus pollen monitoring was carried out simultaneously in five zones of Mexico City. The percentage of Quercus pollen of the total pollen collected from the air showed that the highest concentration was recorded in 2014, followed by 2012. The annual seasonal variation indicated that flowering and pollen emission into the atmosphere began between February and March. The maximum concentration of Quercus pollen was reached at Cuajimalpa. In 2012, the amount of pollen grains was distributed in March and April uniformly, whilst in 2014, the largest amount of pollen was concentrated in March. In 2012 and 2014 (years with the highest pollen concentrations), corresponding intraday variations were quite similar, with a low relative maximum in the morning and the highest concentrations in the evening. The largest values were recorded in 2014, and two processes can explain these. In the afternoon, pollen from secondary forest is carried by southwesterly converging winds, increasing the pollen concentration in Cuajimalpa. In the evening, there is an additional pollen contribution from primary forest via transport by NW winds.

Spatial Epidemiology and Risk Factor Analysis of White Spot Disease in the Shrimp Farming Industry of Sinaloa, Mexico, from 2005 to 2011.

White spot disease (WSD), caused by the white spot syndrome virus, is currently one of the primary causes of mortality and economic losses in the shrimp farming industry worldwide. In Mexico, shrimp production is one of the most important primary activities generating an annual income of USD 711 million. However, WSD introduction in 1999 had a devastating impact for the Mexican shrimp industry. The aim of this study was to characterize the WSD spatio-temporal patterns and to identify the primary risk factors contributing to WSD occurrence from 2005 to 2011 in Sinaloa, Mexico. We used data collected by the 'Comité Estatal de Sanidad Acuícola de Sinaloa' from 2005 to 2011 regarding WSD outbreaks as well as environmental, production and husbandry factors at farm level. The spatio-temporal patterns of WSD were described using space-time scan statistics. The effect of 52 variables on the time to WSD outbreak occurrence was assessed using a multivariable Cox proportional hazards model. Results reveal that WSD risk and survival time were not homogeneously distributed as suggested by the significant clusters obtained using the space-time permutation model and the space-time exponential model, respectively. The Cox model revealed that the first production cycle [hazard ratio (HR) = 11.31], changes from 1 to 1.4°C of temperature oscillation caused by 'El Niño'/'La Niña' events (HR = 1.44) and high average daily growths (HR = 1.26) were significantly associated with lower survival (i.e. shorter time to WSD outbreak) on farm. Conversely, shrimp weight at the moment of the outbreak (HR = 0.159), changes from -0.9 to -0.5°C of temperature oscillation caused by 'El Niño'/'La Niña' events (HR = 0.540), high superficial water temperature during the pound stocking (HR = 0.823) and high (>100) number of days of culture (HR = 0.830) were factors associated with higher survival. Results are expected to inform the design of risk-based, intervention strategies to minimize the impact of WSD in Mexico.

A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru.

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI-II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI-III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I-IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru.

The role of fish movements and the spread of infectious salmon anemia virus (ISAV) in Chile, 2007-2009.

Infectious salmon anemia virus (ISAV) infection is a constant major threat to farmed and wild Atlantic salmon worldwide. Many epidemics have recently been reported in the most important salmon farming regions of the world, including Chile (2007-2009), where ISAV generated the most important disease and economic crisis in history of the salmon industry of the country. The spread of ISAV within a region is most likely by local or neighborhood spread from an infected farm; however, there is evidence that anthropogenic activities, such as movement of live or harvested fish or their byproduct, may have played a more important role than environmental or passive transmission in the 2007-2009 outbreak. Atlantic salmon farms (n=421) were retrospectively followed from stocking to harvesting in southern Chile at the time of the ISAV epidemic (2007-2009). The effect of husbandry and spatial risk factors, in addition to contact-network risk factors, which were obtained from the social network analyses, on time to first ISAV infection was estimated using a multivariable Cox proportional hazards model. Five variables were retained in the final fitted model: co-existing multiple generations on a farm (hazard ratio [HR]=2.585), mean smolt weight at stocking greater than 120g (HR=1.165), farm area (perkm(2)) (HR=1.005), and increased number of shipments entering a farm, i.e. the farm input degree (HR=1.876) were associated with reduced time to infection; whereas time-to-infection was longer for farms located farther from an ongoing ISAV outbreak (HR=0.943). It was demonstrated that movements of latently infected fish resulted in approximately 7 outbreaks, and potentially explain about 6% of the total number of cases during the epidemic. Results from this study provide new information about the mechanisms of spread of ISAV in one the largest documented ISAV epidemics in the world. Findings may be used to support the design and implementation of risk-based surveillance and control programs that may help to prevent, detect and control future ISAV outbreaks.