Analyzing the intrastate and interstate swine movement network in the United States.

Identifying and restricting animal movements is a common approach used to mitigate the spread of diseases between premises in livestock systems. Therefore, it is essential to uncover between-premises movement dynamics, including shipment distances and network-based control strategies. Here, we analyzed three years of between-premises pig movements, which include 197,022 unique animal shipments, 3973 premises, and 391,625,374 pigs shipped across 20 U.S. states. We constructed unweighted, directed, temporal networks at 180-day intervals to calculate premises-to-premises movement distances, the size of connected components, network loyalty, and degree distributions, and, based on the out-going contact chains, identified network-based control actions. Our results show that the median distance between premises pig movements was 74.37 km, with median intrastate and interstate movements of 52.71 km and 328.76 km, respectively. On average, 2842 premises were connected via 6705 edges, resulting in a weak giant connected component that included 91 % of the premises. The premises-level network exhibited loyalty, with a median of 0.65 (IQR: 0.45 - 0.77). Results highlight the effectiveness of node targeting to reduce the risk of disease spread; we demonstrated that targeting 25 % of farms with the highest degree or betweenness limited spread to 1.23 % and 1.7 % of premises, respectively. While there is no complete shipment data for the entire U.S., our multi-state movement analysis demonstrated the value and the needs of such data for enhancing the design and implementation of proactive- disease control tactics.

PrEP to Party: Exploring MSM's PrEP Use and Interest in the Context of Sexually Themed Events.

Sexually themed events present a unique opportunity for scaling up pre-exposure prophylaxis (PrEP) to men who have sex with men (MSM). This study descriptively explored PrEP uptake among MSM who anticipated attending a week-long major South Florida sexually themed event and examined potential facilitators and barriers to PrEP engagement among potential attendees. Of the participating HIV-negative MSM (n = 96), 66.7% were currently taking PrEP. Prior attendance at sexually themed events was significantly associated with current PrEP engagement and almost 75% of HIV-negative MSM not on PrEP reported high interest in taking PrEP if offered for free at future events.

Spatiotemporal relative risk distribution of porcine reproductive and respiratory syndrome virus in the United States.

Porcine reproductive and respiratory syndrome virus (PRRSV) remains widely distributed across the U.S. swine industry. Between-farm movements of animals and transportation vehicles, along with local transmission are the primary routes by which PRRSV is spread. Given the farm-to-farm proximity in high pig production areas, local transmission is an important pathway in the spread of PRRSV; however, there is limited understanding of the role local transmission plays in the dissemination of PRRSV, specifically, the distance at which there is increased risk for transmission from infected to susceptible farms. We used a spatial and spatiotemporal kernel density approach to estimate PRRSV relative risk and utilized a Bayesian spatiotemporal hierarchical model to assess the effects of environmental variables, between-farm movement data and on-farm biosecurity features on PRRSV outbreaks. The maximum spatial distance calculated through the kernel density approach was 15.3 km in 2018, 17.6 km in 2019, and 18 km in 2020. Spatiotemporal analysis revealed greater variability throughout the study period, with significant differences between the different farm types. We found that downstream farms (i.e., finisher and nursery farms) were located in areas of significant-high relative risk of PRRSV. Factors associated with PRRSV outbreaks were farms with higher number of access points to barns, higher numbers of outgoing movements of pigs, and higher number of days where temperatures were between 4°C and 10°C. Results obtained from this study may be used to guide the reinforcement of biosecurity and surveillance strategies to farms and areas within the distance threshold of PRRSV positive farms.

Modelling control strategies against classical swine fever: Influence of traders and markets using static and temporal networks in Ecuador.

Pig farming in Ecuador represents an important economic and cultural sector, challenged by classical swine fever (CSF). Recently, the National Veterinary Service (NVS), has dedicated its efforts to control the disease by implementing pig identification, mandatory vaccination against CSF and movement control. Our objective was to characterise pig premises according to risk criteria, to model the effect of movement restriction strategies and to consider the temporal evolution of the network. Social network analysis (SNA), SIRS (susceptible, infected, recovered, susceptible) network modelling and temporal analysis were used. The network contained 751,003 shipments and 6 million pigs from 2017 to 2019. Participating premises consisted of 144,118 backyard farms, 138 industrial farms, 21,337 traders and 51 markets. The 10 most influential markets, in the Andean highlands, received between 500 and 4600 pigs each week. The 10 most influential traders made about 3 shipments with 17 pigs per week. Simulations without control strategy resulted in an average CSF prevalence of 14.4 %; targeted movement restriction reduced the prevalence to 7.2 %, while with random movement restriction it was 13 %. Targeting the top 10 national traders and markets and one of the high-risk premises in every parish was one of the best strategies with the surveillance infrastructure available, highlighting its major influence and epidemiological importance in the network. When comparing the static network with its temporal counterpart, causal fidelity (c = 0.62) showed a 38 % overestimation in the number of transmission paths, also traversing the network required 4.39 steps, lasting approximately 233 days. In conclusion, NVS surveillance strategies could be more efficient by targeting the most at-risk premises, and in particular, taking into account the temporal information would make the risk assessment much more precise. This information could contribute to implement risk-based surveillance reducing the time to eradicate CSF and other infectious animal diseases.

Network analysis of pig movements in Ecuador: Strengthening surveillance of classical swine fever.

The analysis of domestic pig movements has become useful to understand the disease spread patterns and epidemiology, which facilitates the development of more effective animal diseases control strategies. The aim of this work was to analyse the static and spatial characteristics of the pig network, to identify its trading communities and to study the contribution of the network to the transmission of classical swine fever. In this regard, we used the pig movement records from the National Veterinary Service of Ecuador (2017-2019), using social network analysis and spatial analysis to construct a network with registered premises as nodes and their movements as edges. Furthermore, we also created a network of parishes as its nodes by aggregating their premises movements as edges. The annual network metrics showed an average diameter of 20.33, a number of neighbours of 2.61, a shortest path length of 4.39 and a clustering coefficient of 0.38 (small-world structure). The most frequent movements were to or from markets (55%). Backyard producers made up 89% of the network premises, and the top 2% of parishes (highest degree) contributed to 50% of the movements. The highest frequencies of movements between parishes were in the centre of the country, while the highest frequency of movements to abattoirs was in the south-west. Finally, the pattern of classical swine fever (CSF) disease outbreaks within the Ecuador network was likely the result of network transmission processes. In conclusion, our results represented the first exploratory analysis of domestic pig movements at premise and parish levels. The surveillance system could consider these results to improve its procedures and update the disease control and management policy, and allow the implementation of targeted or risk-based surveillance.

Coupling spatial statistics with social network analysis to estimate distinct risk areas of disease circulation to improve risk-based surveillance.

Most animal disease surveillance systems concentrate efforts in blocking transmission pathways and tracing back infected contacts while not considering the risk of transporting animals into areas with elevated disease risk. Here, we use a suite of spatial statistics and social network analysis to characterize animal movement among areas with an estimated distinct risk of disease circulation to ultimately enhance surveillance activities. Our model utilized equine infectious anemia virus (EIAV) outbreaks, between-farm horse movements, and spatial landscape data from 2015 through 2017. We related EIAV occurrence and the movement of horses between farms with climate variables that foster conditions for local disease propagation. We then constructed a spatially explicit model that allows the effect of the climate variables on EIAV occurrence to vary through space (i.e., non-stationary). Our results identified important areas in which in-going movements were more likely to result in EIAV infections and disease propagation. Municipalities were then classified as having high 56 (11.3%), medium 48 (9.66%), and low 393 (79.1%) spatial risk. The majority of the movements were between low-risk areas, altogether representing 68.68% of all animal movements. Meanwhile, 9.48% were within high-risk areas, and 6.20% were within medium-risk areas. Only 5.37% of the animals entering low-risk areas came from high-risk areas. On the other hand, 4.91% of the animals in the high-risk areas came from low- and medium-risk areas. Our results demonstrate that animal movements and spatial risk mapping could be used to make informed decisions before issuing animal movement permits, thus potentially reducing the chances of reintroducing infection into areas of low risk.

Multiple species animal movements: network properties, disease dynamics and the impact of targeted control actions.

Infectious diseases in livestock are well-known to infect multiple hosts and persist through a combination of within- and between-host transmission pathways. Uncertainty remains about the epidemic dynamics of diseases being introduced on farms with more than one susceptible host species. Here, we describe multi-host contact networks and elucidate the potential of disease spread through farms with multiple hosts. Four years of between-farm animal movement among all farms of a Brazilian state were described through a static and monthly snapshot of network representations. We developed a stochastic multilevel model to simulate scenarios in which infection was seeded into single host and multi-host farms to quantify disease spread potential, and simulate network-based control actions used to evaluate the reduction of secondarily infected farms. We showed that the swine network was more connected than cattle and small ruminants in both the static and monthly snapshots. The small ruminant network was highly fragmented, however, contributed to interconnecting farms, with other hosts acting as intermediaries throughout the networks. When a single host was initially infected, secondary infections were observed across farms with all other species. Our stochastic multi-host model demonstrated that targeting the top 3.25% of the farms ranked by degree reduced the number of secondarily infected farms. The results of the simulation highlight the importance of considering multi-host dynamics and contact networks while designing surveillance and preparedness control strategies against pathogens known to infect multiple species.

Evaluation of the performance of slaughterhouse surveillance for bovine tuberculosis detection in Castilla y Leon, Spain.

Post-mortem inspection (PMI) of routinely slaughtered cattle in abattoirs is an extremely valuable tool for detecting bovine tuberculosis (bTB) infected herds that can supplement active surveillance activities. However, its true performance is difficult to assess due to the multiple factors that may affect it. Here, we determined relative efficiencies in the detection of bTB-compatible lesions and probabilities of subsequent laboratory confirmation of abattoirs located in Castilla y Leon, one of the regions with the largest cattle population in Spain, between 2010 and 2017. The slaughtered animal population was split based on the results of the ante-mortem tests (reactors or non-reactors), and two generalized linear multivariable mixed models were fitted to each subpopulation to calculate the risk of lesion detection and laboratory confirmation per abattoir while accounting for the effect of potential confounding variables. Throughout the 8-year period, ∼30,000 reactors and >2.8 million non-reactor animals in the ante-mortem tests were culled in the abattoirs under study. Bovine TB compatible lesions were detected in 4,710 (16%) reactors and 828 (0.03%) non-reactor animals, of which >95% were confirmed as infected through bacteriology. The probability of disclosure of bTB-like lesions was associated with the animal subpopulation, type of source unit, the herd size, the year of slaughter, the breed and age of the animal, and/or the season of slaughter. The probabilities of detection of bTB-like lesions varied largely depending on the abattoir in both subpopulations, ranging from 603 to 3,070 per 10,000 animals for the reactors and 0.2-16.1 per 10,000 animals for the non-reactor animals. Results obtained here will help to quantify the performance of PMI in abattoirs in Castilla y Leon and the between-abattoir variability, and to identify animals at increased risk of having bTB-like lesions detected during PMI based on animal- and farm-related factors.

Spatio-temporal network analysis of pig trade to inform the design of risk-based disease surveillance.

Network analysis is a powerful tool to describe, estimate, and predict the role of pig trade in the spread of pathogens and generate essential patterns that can be used to understand, prevent, and mitigate possible outbreaks. This study aimed to describe the network between premises such as production herds, slaughterhouses, and traders of pig movements and identify heterogeneities in the connectivity of premises in the state of Santa Catarina, Brazil, using social network analysis (SNA). We used static and temporal network approaches to describe pig trade in the state by quantifying network attributes using SNA parameters, such as causal fidelity, loyalty, the proportion of node-loyalty, resilience of outgoing contact chains, and communities. Two indexes were implemented, the first one is a normalized index based on SNA-farm level measures and other index-based SNA-farm level measures considering the swineherd population size from all premises, both indexes were summarized by a municipality to target and rank surveillance activities. Within Santa Catarina, the southwest region played a key role in that 80 % of trade was concentrated in this region, and thus acted as a hub in the network. Besides, nine communities were found. The results also showed that premises were highly connected in the static network, with the network exhibiting low levels of fragmentation and loyalty. Also, just 11 % of the paths in the static network existed in the temporal network which accounted for the order in which edges occurred. Therefore, the use of time-respecting-paths was essential to not overestimate potential transmission pathways and outbreak sizes. Compared to static networks, the application of temporal network approaches was more suitable to capture the dynamics of pig trade and should be used to inform the design of riskbased disease surveillance.

Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil.

Livestock movements create complex dynamic interactions among premises that can be represented, interpreted, and used for epidemiological purposes. These movements are a very important part of the production chain but may also contribute to the spread of infectious diseases through the transfer of infected animals over large distances. Social network analysis (SNA) can be used to characterize cattle trade patterns and to identify highly connected premises that may act as hubs in the movement network, which could be subjected to targeted control measures in order to reduce the transmission of communicable diseases such as bovine tuberculosis (TB). Here, we analyzed data on cattle movement and slaughterhouse surveillance for detection of TB-like lesions (TLL) over the 2016-2018 period in the state of Rio Grande do Sul (RS) in Brazil with the following aims: (i) to characterize cattle trade describing the static full, yearly, and monthly snapshots of the network contact trade, (ii) to identify clusters in the space and contact networks of premises from which animals with TLL originated, and (iii) to evaluate the potential of targeted control actions to decrease TB spread in the cattle population of RS using a stochastic metapopulation disease transmission model that simulated within-farm and between-farm disease spread. We found heterogeneous densities of premises and animals in the study area. The analysis of the contact network revealed a highly connected (~94%) trade network, with strong temporal trends, especially for May and November. The TLL cases were significantly clustered in space and in the contact network, suggesting the potential for both local (e.g., fence-to-fence) and movement-mediated TB transmission. According to the disease spread model, removing the top 7% connected farms based on degree and betweenness could reduce the total number of infected farms over three years by >50%. In conclusion, the characterization of the cattle network suggests that highly connected farms may play a role in TB dissemination, although being close to infected farms was also identified as a risk factor for having animals with TLL. Surveillance and control actions based on degree and betweenness could be useful to break the transmission cycle between premises in RS.

Quantifying the dynamics of pig movements improves targeted disease surveillance and control plans.

Tracking animal movements over time may fundamentally determine the success of disease control interventions. In commercial pig production growth stages determine animal transportation schedule, thus it generates time-varying contact networks showed to influence the dynamics of disease spread. In this study, we reconstructed pig networks of one Brazilian state from 2017 to 2018, comprising 351,519 movements and 48 million transported pigs. The static networks view did not capture time-respecting movement pathways. For this reason, we propose a time-dependent network approach. A susceptible-infected model was used to spread an epidemic over the pig network globally through the temporal between-farm networks, and locally by a stochastic model to account for within-farm dynamics. We propagated disease to calculate the cumulative contacts as a proxy of epidemic sizes and evaluate the impact of network-based disease control strategies in the absence of other intervention alternatives. The results show that targeting 1,000 farms ranked by degree would be sufficient and feasible to diminish disease spread considerably. Our modelling results indicated that independently from where initial infections were seeded (i.e. independent, commercial farms), the epidemic sizes and the number of farms needed to be targeted to effectively control disease spread were quite similar; indeed, this finding can be explained by the presence of contact among all pig operation types The proposed strategy limited the transmission the total number of secondarily infected farms to 29, over two simulated years. The identified 1,000 farms would benefit from enhanced biosecurity plans and improved targeted surveillance. Overall, the modelling framework provides a parsimonious solution for targeted disease surveillance when temporal movement data are available.

Risk factors associated with Leishmania exposure among dogs in a rural area of Ilha Solteira, SP, Brazil.

INTRODUCTION: We sought to determine risk factors (RFs) associated with the presence of antibodies against Leishmania in dogs from a rural area of Ilha Solteira, SP, Brazil. METHODS: Serum samples were collected from 250 dogs and tested using indirect enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence antibody tests (IFATs). Data concerning dogs, their environment, and their owners' knowledge of leishmaniasis were collected using a questionnaire. To determine RFs for contact with the parasite, univariate statistical analysis based on chi-squared and Fisher's exact tests, followed by logistic regression, was used. RESULTS: It was found that 79/250 (31.6%) of the dogs were positive by IFAT, and 72/250 (28.8%) by ELISA. A total of 82/250 dogs (32.8%) were positive in at least one test. The RFs associated with occurrences of Leishmania exposure were large body size (OR = 2.25; 95% CI = 1.26-4.04; p = 0.003), presence of chickens (OR = 1.94; 95% CI = 1.05-3.65; p = 0.023), and lack of knowledge about Leishmania among dog owners (OR = 1.74; 95% CI = 0.96-3.21; p = 0.049). After multivariate analysis, the RFs for occurrence of Leishmania exposure in dogs that remained significantly associated were the dog's size (large dogs) (OR = 1.2; 95% CI = 1.06-1.35; p = 0.003) and presence of chickens on the properties (small farms) (OR = 1.15; 95% CI = 1.02-1.30; p = 0.023). CONCLUSIONS: These results may be useful for improving preventive practices to reduce the incidence of Leishmania exposure among dogs in rural areas.

Risk factors associated with Leishmania exposure among dogs in a rural area of Ilha Solteira, SP, Brazil

Abstract INTRODUCTION: We sought to determine risk factors (RFs) associated with the presence of antibodies against Leishmania in dogs from a rural area of Ilha Solteira, SP, Brazil. METHODS: Serum samples were collected from 250 dogs and tested using indirect enzyme-linked immunosorbent assay (ELISA) and indirect immunofluorescence antibody tests (IFATs). Data concerning dogs, their environment, and their owners' knowledge of leishmaniasis were collected using a questionnaire. To determine RFs for contact with the parasite, univariate statistical analysis based on chi-squared and Fisher's exact tests, followed by logistic regression, was used. RESULTS: It was found that 79/250 (31.6%) of the dogs were positive by IFAT, and 72/250 (28.8%) by ELISA. A total of 82/250 dogs (32.8%) were positive in at least one test. The RFs associated with occurrences of Leishmania exposure were large body size (OR = 2.25; 95% CI = 1.26-4.04; p = 0.003), presence of chickens (OR = 1.94; 95% CI = 1.05-3.65; p = 0.023), and lack of knowledge about Leishmania among dog owners (OR = 1.74; 95% CI = 0.96-3.21; p = 0.049). After multivariate analysis, the RFs for occurrence of Leishmania exposure in dogs that remained significantly associated were the dog's size (large dogs) (OR = 1.2; 95% CI = 1.06-1.35; p = 0.003) and presence of chickens on the properties (small farms) (OR = 1.15; 95% CI = 1.02-1.30; p = 0.023). CONCLUSIONS: These results may be useful for improving preventive practices to reduce the incidence of Leishmania exposure among dogs in rural areas.

Burkholderia mallei: The dynamics of networks and disease transmission.

Glanders is a highly infectious zoonotic disease caused by Burkholderia mallei. The transmission of B. mallei occurs mainly by direct contact, and horses are the natural reservoir. Therefore, the identification of infection sources within horse populations and animal movements is critical to enhance disease control. Here, we analysed the dynamics of horse movements from 2014 to 2016 using network analysis in order to understand the flow of animals in two hierarchical levels, municipalities and farms. The municipality-level network was used to investigate both community clustering and the balance between the municipality's trades and the farm-level network associations between B. mallei outbreaks and the network centrality measurements, analysed by spatio-temporal generalized additive model (GAM). Causal paths were established for the dispersion of B. mallei outbreaks through the network. Our approach captured and established a direct relationship between movement of infected equines and predicted B. mallei outbreaks. The GAM model revealed that the parameters in degree and closeness centrality out were positively associated with B. mallei. In addition, we also detected 10 communities with high commerce among municipalities. The role of each municipality within the network was detailed, and significant changes in the structures of the network were detected over the course of 3 years. The results suggested the necessity to focus on structural changes of the networks over time to better control glanders disease. The identification of farms with a putative risk of B. mallei infection using the horse movement network provided a direct opportunity for disease control through active surveillance, thus minimizing economic losses and risks for human cases of B. mallei.

Seroprevalence of Leptospira spp infection and its risk factors among domestic dogs in Bogotá, Colombia.

Different analytical tools were used to determine the seroprevalence of and risk factors associated with Leptospira spp infection in 192 domestic dogs (Canis familiaris) in Bogotá, Colombia. Using the microscopic agglutination test (MAT), a battery of 16 Leptospira serovars were tested. The seroprevalence of Leptospira spp was calculated as 36.46% (95% CI 0.30-0.43). A questionnaire was applied to the dogs' owners at the time of sampling and the variables "Water sources near home" and "Dog hunting rodents" were identified as risk factors for leptospirosis occurrence in the urban area of Bogotá. Geographical coordinates relating to the dogs' households were obtained in order to map out the spatial distribution of reactive and unreactive dogs. Additionally, we found that the mean annual precipitation was higher at geographical locations with reactive animals than at those with unreactive dogs (p < 0.05). Preventing exposure of dogs to rodents and waste-water bodies that could be contaminated with Leptospira might effectively reduce occurrences of leptospirosis. Moreover, promoting preventive programs and vaccination of dogs against leptospirosis in areas of higher precipitation and prior to rainy months could be an effective strategy for leptospirosis prevention.

Isolation and identification of Mycobacterium bovis in bovines with positive reaction to the tuberculin test in the state of Paraíba, northeast Brazil / Isolamento e identificação de Mycobacterium bovis em bovinos positivos no teste de tuberculinização no estado da Paraíba, nordeste do Brasil

In areas where human tuberculosis and bovine tuberculosis coexist, differentiation between M. bovis and M. tuberculosis is important for monitoring the spread of M. bovis among cattle and from cattle to humans. The objective of this study was to isolate and identify M. bovis in bovines with positive diagnosis identified on tuberculin test in the State of Paraíba, Northeastern Brazil. Thirty-two bovines that tested positive in the comparative tuberculin test were used, from which samples of any organ with lesions suggestive of tuberculosis were collected, as well as lymph nodes, when no gross lesions were observed. Samples were submitted to histopathological exam, mycobacterial culture, Ziehl-Neelsen staining and molecular diagnosis. Twenty-one (65.6%) animals presented lesions suggestive of tuberculosis. As to body region 77.7% of lesions were found in the thoracic cavity, 12.4% in the head and 9.9% in the abdominal cavity. Among 55 samples submitted to mycobacterial culture, mycobacteria were isolated in 31 (56.4%), being 13 (41.9%) identified as M. bovis and 18 (58.1%) as Mycobacterium spp. Conclusion is that isolation and identification of M. bovis and Mycobacterium spp. in cattle suggests that humans are exposed to the risk of infection. This reinforces the need for intensification and optimization of prevention and control measures foreseen in the Brazilian National Program for the Control and Eradication of Bovine Brucellosis and Tuberculosis. Mycobacteria isolation and identification surveys are, therefore, encouraged in other Northeastern states.(AU)

Em áreas onde a tuberculose humana e a tuberculose bovina coexistem, a diferenciação entre M. bovis e M. tuberculosis é importante para monitorar a disseminação de M. bovis entre bovinos e destes para os seres humanos. Objetivou-se neste estudo isolar e identificar M. bovis em bovinos com diagnóstico positivo pelo teste de tuberculinização no estado da Paraíba, nordeste do Brasil. Foram submetidos 32 bovinos positivos ao teste de tuberculinização comparativa, dos quais foram colhidas amostras de qualquer órgão com lesões sugestivas de tuberculose, e, nos casos em que não foram observadas lesões sugestivas, foram colhidas amostras de linfonodos. As amostras foram submetidas a exame histopatológico, cultivo micobacteriológico, coloração de Ziehl-Neelsen e diagnóstico molecular. Apresentaram lesões sugestivas de tuberculose 21 animais (65,6%). Com relação à distribuição das lesões de acordo com a região corporal, 77,7% localizavam-se na cavidade torácica, 12,4% na cabeça e 9,9% na cavidade abdominal. De 55 amostras submetidas ao cultivo de micobactérias, em 31 (56,4%) foram isoladas micobactérias, sendo que em 13 (41,9%) foi identificado M. bovis, e nas 18 restantes (58,1%) foi identificado Mycobacterium spp. Conclui-se que o isolamento e a identificação de M. bovis e Mycobacterium spp. em bovinos indicam que os seres humanos estão expostos ao risco de infecção. Isso reforça a necessidade de intensificação e otimização de medidas de prevenção e controle previstas no Programa Nacional de Controle e Erradicação da Brucelose e Tuberculose Bovina. Sugere-se a realização de estudos de isolamento e identificação de micobactérias em outros estados do Nordeste.(AU)

Estudio multicéntrico y comparativo de la eficacia y seguridad de cefprozil 30 mg/kg/día vs cefprozil 50 mg/kg/día en otitis media aguda (OMA) y sinusitis aguda (SA) en pacientes pediátricos / Study multicentric and comparative of the efficacy and segurity of cefprozil 30 mg/kg/day vs cefprozil 50 mg/kg/day in otitis media acute (OMA) and sinusitis acute (SA) in patients pediatric

La resistencia bacteriana a antibióticos causa fracaso terapéutico y una de sus causas es la dosificación subterapéutica de los mismos. Por ello, con base en su eficacia y seguridad, se valoran dos regímenes diferentes de Cefprozil (30 o 50 mg/kg/día) para el tratamiento de OMA y SA en niños. Para ello, se reclutaron a 277 niños menores de 12 años, 193 de los cuales recibieron 30 mg/kg/día de Cefprozil y el resto (84) 50 mg/kg/día del mismo antibiótico. La eficacia, definida por curación o mejoría, fue de 81 por ciento en el primer grupo y de 95 por ciento en el segundo en OMA. La eficacia de la dosis de 50 mg/kg/día de Cefprozil fue estadísticamente superior a la observada con 30 mg/kg/día, cuya significancia fue de p=0,01 por X², resultados superiores a los observados en estudios internacionales con otros medicamentos comúnmente utilizados para tratar estas patologías

Estudio comparativo entre una fórmula de aceite mineral vs. un champú de pediculicida para el tratamiento de la infestación por piojos / Comparative study with one formula of mineral oil vs. one shampoo with the treatment of the louse infection

La infestación por piojos se ha hecho difícil de curar con pediculicidas de uso común por la aparición de resistencia a los insecticidas. La aplicación tópica de sustancias oleosas que actúan como sofocantes ha sido reportada anecdóticamente como un tratamiento efectivo y exento de efectos adversos. El objetivo del presente estudio fue comparar una loción de aceite mineral vs. un champú pediculicida de tetrametrina y butóxido de piperonilo en el tratamiento de la infestación por Pediculus capitis. Se realizó un estudio comparativo, abierto, no aleatorio, en una muestra de 44 niñas de un preescolar de Caracas infestadas por Pediculus capitis. El grupo experimental (n=22) recibió aceite mineral y el grupo control (n=22) recibió champú pediculicida según las indicaciones de los fabricantes. Se consideró curada a la paciente que no presentaba piojos después de revisiones sucesivas durante 2 semanas. La curación lograda con aceite mineral fue 100 por ciento [IC95 por ciento: 82 por ciento-100 por ciento] y 27 por ciento [IC95 por ciento: 11 por ciento-50 por ciento] con el champú pediculicida (p<0,001). El aceite mineral eliminó las liendres en 86 por ciento [IC95 por ciento: 64 por ciento-96 por ciento] de los sujetos y, el champú pediculicida en 36 por ciento [IC95 por ciento: 18 por ciento-59 por ciento] (p=0,0007). Se reportaron efectos desfavorables asociados al champú pediculicida en 36 por ciento [IC95 por ciento: 18 por ciento-59 por ciento] de los sujetos y asociados al aceite mineral en 0 por ciento [IC95 por ciento: 0 por ciento-19 por ciento] (p=0,003). El aceite mineral fue considerado excelente o bueno por 100 por ciento [IC95 por ciento: 82 por ciento-100 por ciento] de los sujetos y el champú pediculicida por 17 por ciento [IC95 por ciento: 5 por ciento-40 por ciento] (p<0,0001). En conclusión una loción de aceite mineral es más efectiva, más segura y mejor aceptada que un champú pediculicida de tetramentrina y butóxido de piperonilo en el tratamiento de la infestación por piojos