Is Participation Contagious? Evidence From a Household Vector Control Campaign in Urban Peru

Objective: High rates of household participation are critical to the success of door-to-door vector control campaigns. We used the Health Belief Model to assess determinants of participation, including neighbour participation as a cue to action, in a Chagas disease vector control campaign in Peru. Methods: We evaluated clustering of participation among neighbours; estimated participation as a function of household infestation status, neighbourhood type and number of participating neighbours; and described the reported reasons for refusal to participate in a district of 2911 households. Results: We observed significant clustering of participation along city blocks (p\u3c0.0001). Participation was significantly higher for households in new versus established neighbourhoods, for infested households, and for households with more participating neighbours. The effect of neighbour participation was greater in new neighbourhoods. Conclusions: Results support a ‘contagion’ model of participation, highlighting the possibility that one or two participating households can tip a block towards full participation. Future campaigns can leverage these findings by making participation more visible, by addressing stigma associated with spraying, and by employing group incentives to spray

The Effects of City Streets on an Urban Disease Vector.

With increasing urbanization vector-borne diseases are quickly developing in cities, and urban control strategies are needed. If streets are shown to be barriers to disease vectors, city blocks could be used as a convenient and relevant spatial unit of study and control. Unfortunately, existing spatial analysis tools do not allow for assessment of the impact of an urban grid on the presence of disease agents. Here, we first propose a method to test for the significance of the impact of streets on vector infestation based on a decomposition of Moran’s spatial autocorrelation index; and second, develop a Gaussian Field Latent Class model to finely describe the effect of streets while controlling for cofactors and imperfect detection of vectors. We apply these methods to cross-sectional data of infestation by the Chagas disease vector Triatoma infestans in the city of Arequipa, Peru. Our Moran’s decomposition test reveals that the distribution of T. infestans in this urban environment is significantly constrained by streets (p,0.05). With the Gaussian Field Latent Class model we confirm that streets provide a barrier against infestation and further show that greater than 90% of the spatial component of the probability of vector presence is explained by the correlation among houses within city blocks. The city block is thus likely to be an appropriate spatial unit to describe and control T. infestans in an urban context. Characteristics of the urban grid can influence the spatial dynamics of vector borne disease and should be considered when designing public health policies

Is Participation Contagious? Evidence From a Household Vector Control Campaign in Urban Peru

Objective: High rates of household participation are critical to the success of door-to-door vector control campaigns. We used the Health Belief Model to assess determinants of participation, including neighbour participation as a cue to action, in a Chagas disease vector control campaign in Peru. Methods: We evaluated clustering of participation among neighbours; estimated participation as a function of household infestation status, neighbourhood type and number of participating neighbours; and described the reported reasons for refusal to participate in a district of 2911 households. Results: We observed significant clustering of participation along city blocks (p\u3c0.0001). Participation was significantly higher for households in new versus established neighbourhoods, for infested households, and for households with more participating neighbours. The effect of neighbour participation was greater in new neighbourhoods. Conclusions: Results support a ‘contagion’ model of participation, highlighting the possibility that one or two participating households can tip a block towards full participation. Future campaigns can leverage these findings by making participation more visible, by addressing stigma associated with spraying, and by employing group incentives to spray

Residual infestation and recolonization during urban Triatoma infestans Bug Control Campaign, Peru

Chagas disease vector control campaigns are being conducted in Latin America, but little is known about medium-term or long-term effectiveness of these efforts, especially in urban areas. After analyzing entomologic data for 56,491 households during the treatment phase of a Triatoma infestans bug control campaign in Arequipa, Peru, during 2003-2011, we estimated that 97.1% of residual infestations are attributable to untreated households. Multivariate models for the surveillance phase of the campaign obtained during 2009-2012 confirm that nonparticipation in the initial treatment phase is a major risk factor (odds ratio [OR] 21.5, 95% CI 3.35-138). Infestation during surveillance also increased over time (OR 1.55, 95% CI 1.15-2.09 per year). In addition, we observed a negative interaction between nonparticipation and time (OR 0.73, 95% CI 0.53-0.99), suggesting that recolonization by vectors progressively dilutes risk associated with nonparticipation. Although the treatment phase was effective, recolonization in untreated households threatens the long-term success of vector control

Spatial distribution of <i>Triatoma infestans</i> presence in households of Paucarpata, Arequipa, Peru.

<p>Map of the study area. Black indicates infested households, white non-infested households, and grey non-inspected households. The area encircled by dashes was used to fit the Gaussian Field Latent Class model; the remaining area was used as a validation dataset. The close-up shows the urban grid underneath and the aggregation of vectors within city blocks.</p

Spatial autocorrelation of data simulated with the Gaussian Field Latent Class model of <i>Triatoma infestans</i> distribution.

<p>The autocorrelation of infestation in the generated data is compared to the autocorrelation in observed data. Infestation data were generated on the validation map using the estimated parameters for each of the kernels: exponential (first column), Cauchy (second column), Gaussian (third column), and geometric (fourth column). We calculated the standard Moran's I (first row) and the difference between within block and across street autocorrelation (second row) as a function of distance. The solid line indicates the values for the observed data. Box plots indicate the values obtained from generated data. The boxes indicate the , and quantiles, and the whiskers depict the 95% CrI.</p

General structure of the Gaussian Field Latent Class model.

<p>Working backward, we consider the infestation data to be the result of a latent infestation status , observed by imperfect inspectors of sensitivity . The true infestation is a binary manifestation of an underlying continuous infestation predictor . Cofactors and a local error term, , form the local component. The spatial component is modeled as a Gaussian field. The fit parameters, and , respectively tune how distances between neighbors and the streets define the spatial dependency between households in the spatial component.</p

Spatial autocorrelation of <i>Triatoma infestans</i> presence in Paucarpata, Arequipa, Peru and the effects of streets.

<p>Left: autocorrelation of the infestation status as a function of the distance. Solid line: Global Moran's index. Dot-Dashed line: Moran's Index for within blocks household pairs. Dashed line: Moran's Index for household pairs across streets. All Moran's I values are significantly different from the expected value under hypothesis of no spatial autocorrelation (). Right: significance of the difference between the correlation within city blocks and the correlation across streets. Box plots indicate the expected values under the null hypothesis using a permutation test. The boxes indicate the , and quantiles, and the whiskers depict the 95% CrI.</p

Spatial kernels and corresponding fitted parameters.

a<p>The shape factor is indicated in meters.</p>b<p>Same Block Index: Percent of the spatial component of infestation explained by same city block neighbors (see Section 2 in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002801#pcbi.1002801.s003" target="_blank">Text S1</a>). In parentheses are the 95% Credible Intervals (CrI) according to the MCMC sampling. The probability of having no barrier effect of streets is indicated with the values of : ;</p>***<p>.</p

Circulating microRNA after autologous bone marrow mononuclear cell (BM-MNC) injection in patients with ischemic stroke

Previous studies have shown the potential of microRNAs (miRNA) in the pathological process of stroke and functional recovery. Bone marrow mononuclear cell (BM-MNC) transplantation improves recovery in experimental models of ischemic stroke that might be related with miRNA modifications. However, its effect on circulating miRNA has not been described in patients with stroke. We aimed to evaluate the circulating levels of miRNAs after autologous BM-MNC transplantation in patients with stroke. We investigate the pattern of miRNA-133b and miRNA-34a expression in patients with ischemic stroke included in a multicenter randomized controlled phase IIb trial (http://www.clinicaltrials.gov; unique identifier: NCT02178657). Patients were randomized to 2 different doses of autologous intra-arterial BM-MNC injection (2×106/kg or 5×106/kg) or control group within the first 7 days after stroke onset. We evaluate plasma concentration of miRNA-113b and miRNA-34a at inclusion and 4, 7, and 90 days after treatment. Thirteen cases (8 with 2×106/kg BM-MNC dose and 5 with 5×106/kg dose) and 11 controls (BM-MNC non-treated) were consecutively included. Mean age was 64.1±12.3 with a mean National Institutes of Health Stroke Scale score at inclusion of 14.5. Basal levels of miRNA were similar in both groups. miR-34a-5p and miR-133b showed different expression patterns. There was a significant dose-dependent increase of miRNA-34a levels 4 days after BM-MNC injection (fold change 3.7, p<0.001), whereas miRNA-133b showed a significant increase in the low-dose BM-MNC group at 90 days. Intra-arterial BM-MNC transplantation in patients with ischemic stroke seems to modulate early circulating miRNA-34a levels, which have been related to precursor cell migration in stroke and smaller infarct volumes.This work has been supported by the grants PI15/01197, PI18/01414 and RD16/0019/0015 (INVICTUS+) from the Spanish Ministry of Economy and Competitiveness, cofunded by ISCIII and FEDER funds; Mutua Madrileña grant. FMa is supported by a Rio Hortega contract (CM16/00015). Andalusian Initiative for Advanced Therapies (IATA) is the sponsor of the trial