Spatial spillovers and political coordination in public health provision

We estimate the impact of the main unconditional federal grant (Fundo de Participaçãodos Municípios - FPM) to Brazilian municipalities as well as its spillover from the neighboring cities on local health outcomes. We consider data from 2002 to 2007 (Brollo et al, 2013) and explore the FPM distribution rule according to population brackets to apply a fuzzy Regression Discontinuity Design (RDD) using cities near the thresholds. In elasticity terms, we nd a reduction on infant mortality rate (-0.18) and on morbidity rate (- 0.41), except in the largest cities of our sample. We also nd an increase on the access to the main program of visiting the vulnerable families, the Family Health Program (Programa Sa ude da Família - PSF). The e ects are stronger for the smallest cities of our sample and we nd increase: (i) On the percentage of residents enrolled in the program (0.36), (ii) On the per capita number of PSF visits (1.59), and (iii) On the per capita number of PSF visits with a doctor (1.8) and nurse (2). After we control for the FPM spillover using neighboring cities near diferent thresholds, our results show that the reduction in morbidity and mortality is largely due to the spillover e ect, but there are negative spillover on preventive actions, as PSF doctors visits and vaccination. Finally, the negative spillover e ect on health resources may be due free riding or political coordination problems, as in the case of the number of hospital beds, but also due to to competition for health professionals, as in the case of number of doctors (-0.35 and -0.87, respectively), specially general practitioners and surgeons (-1.84 and -2.45).

Mortality Risk in Insects

Understanding how and why insect numbers fluctuate through time and space has been a central theme in ecological research for more than a century. Life tables have been used to understand temporal and spatial patterns in insect numbers. In this study, we estimated cause-of-death probabilities for phytophagous insects using multiple decrement life tables and the irreplaceable mortality analytic technique. Multiple decrement life tables were created from 73 insect life tables published from 1954 to 2004. Irreplaceable mortality (the portion of mortality that cannot be replaced by another cause) from pathogens, predators, and parasitoids was 8.6 +/- 7.2, 7.8 +/- 4.9, and 6.2 +/- 1.6%, respectively. In contrast, the mean irreplaceable mortality from all non-natural enemy mortality factors (mortality from factors other than natural enemies) was 35.1 +/- 4.4%. Irreplaceable mortality from natural enemies was significantly lower compared with non-natural enemy factors. Our results may partially explain cases of unsuccessful efficacy in classical biological control, after successful establishment, by showing low irreplaceable mortality for natural enemies, including 5.2 +/- 1.6% for introduced natural enemies. We suggest that the environment (i.e., the degree of environmental stability) influences the magnitude of the irreplaceable mortality from natural enemies. Our results lead to several testable hypotheses and emphasize that it is not possible to estimate the effect of any mortality factor without considering its interaction with competing mortality factors, which has far-reaching consequences for population biology and applied ecology.

Distribution of paracoccidioidomycosis: determination of ecologic correlates through spatial analyses

Paracoccidioidomycosis (PCM) is endemic in Latin America and in countries like Brazil it carries a high mortality rate. The fungus' habitat has not been precisely determined. The present study aims to identify ecologic correlates based on PCM distribution in a hyper-endemic area in southeastern Brazil. The Geographic Information System (GIS) and spatial statistics were used to associate environmental attributes, human population density and, PCM distribution. By means of the Pearson r correlation coefficient, the highest statistically significant associations with prevalence density were the percent area (by county) of: basaltic rocks (r = 0.63; P < 0.0001), Podzolic soils (r = - 0.48; P < 0.001), Latosol soils (r = 0.40; P < 0.01), mean annual precipitation between 1500 and 1600 mm (r = 0.46; P < 0.001) and, mean precipitation during the wet season between 940 and 1040 mm (r = - 0.44; P < 0.01). Soil texture and precipitation analyzed together reached r = 0.61 (P < 0.000002) for fine-textured soils with annual precipitation above 1400 mm. Environmental correlates indicate that moisture availability plays an important role in PCM distribution.

Spatial and temporal variation in population structure of Hemigrammus marginatus (Characiformes: Characidae) in streams of the Ivinhema River Basin, Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Temporal, spatial and spatiotemporal analysis of the occurrence of visceral leishmaniasis in humans in the City of Birigui, State of São Paulo, from 1999 to 2012

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Community-wide spatial and temporal discordances of seed-seedling shadows in a tropical rainforest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The impact of atmospheric particulate matter on cancer incidence and mortality in the city of Sao Paulo, Brazil

This study aimed to verify the impact of inhalable particulate matter (PM10) on cancer incidence and mortality in the city of Sao Paulo, Brazil. Statistical techniques were used to investigate the relationship between PM10 on cancer incidence and mortality in selected districts. For some types of cancer (skin, lung, thyroid, larynx, and bladder) and some periods, the correlation coefficients ranged from 0.60 to 0.80 for incidence. Lung cancer mortality showed more correlations during the overall period. Spatial analysis showed that districts distant from the city center showed higher than expected relative risk, depending on the type of cancer According to the study, urban PM10 can contribute to increased incidence of some cancers and may also contribute to increased cancer mortality. The results highlight the need to adopt measures to reduce atmospheric PM10 levels and the importance of their continuous monitoring.

Suicide rates and income in Sao Paulo and Brazil: a temporal and spatial epidemiologic analysis from 1996 to 2008

Background: In a classical study, Durkheim noted a direct relation between suicide rates and wealth in the XIX century France. Since that time, several studies have verified this relationship. It is known that suicide rates are associated with income, although the direction of this association varies worldwide. Brazil presents a heterogeneous distribution of income and suicide across its territory; however, evaluation for an association between these variables has shown mixed results. We aimed to evaluate the relationship between suicide rates and income in Brazil, State of Sao Paulo (SP), and City of SP, considering geographical area and temporal trends. Methods: Data were extracted from the National and State official statistics departments. Three socioeconomic areas were considered according to income, from the wealthiest (area 1) to the poorest (area 3). We also considered three regions: country-wide (27 Brazilian States and 558 Brazilian micro-regions), state-wide (645 counties of SP State), and city-wide (96 districts of SP city). Relative risks (RR) were calculated among areas 1, 2, and 3 for all regions, in a cross-sectional approach. Then, we used Joinpoint analysis to explore the temporal trends of suicide rates and SaTScan to investigate geographical clusters of high/low suicide rates across the territory. Results: Suicide rates in Brazil, the State of SP, and the city of SP were 6.2, 6.6, and 5.4 per 100,000, respectively. Taking suicide rates of the poorest area (3) as reference, the RR for the wealthiest area was 1.64, 0.88, and 1.65 for Brazil, State of SP, and city of SP, respectively (p for trend <0.05 for all analyses). Spatial cluster of high suicide rates were identified at Brazilian southern (RR = 2.37), state of SP western (RR = 1.32), and city of SP central (RR = 1.65) regions. A direct association between income and suicide were found for Brazil (OR = 2.59) and the city of SP (OR = 1.07), and an inverse association for the state of SP (OR = 0.49). Conclusions: Temporospatial analyses revealed higher suicide rates in wealthier areas in Brazil and the city of SP and in poorer areas in the State of SP. We further discuss the role of socioeconomic characteristics for explaining these discrepancies and the importance of our findings in public health policies. Similar studies in other Brazilian States and developing countries are warranted.

Spatial clusters of suicide in the municipality of Sao Paulo 1996-2005: an ecological study

Background: In a classical study, Durkheim mapped suicide rates, wealth, and low family density and realized that they clustered in northern France. Assessing others variables, such as religious society, he constructed a framework for the analysis of the suicide, which still allows international comparisons using the same basic methodology. The present study aims to identify possible significantly clusters of suicide in the city of Sao Paulo, and then, verify their statistical associations with socio-economic and cultural characteristics. Methods: A spatial scan statistical test was performed to analyze the geographical pattern of suicide deaths of residents in the city of Sao Paulo by Administrative District, from 1996 to 2005. Relative risks and high and/or low clusters were calculated accounting for gender and age as co-variates, were analyzed using spatial scan statistics to identify geographical patterns. Logistic regression was used to estimate associations with socioeconomic variables, considering, the spatial cluster of high suicide rates as the response variable. Drawing from Durkheim's original work, current World Health Organization (WHO) reports and recent reviews, the following independent variables were considered: marital status, income, education, religion, and migration. Results: The mean suicide rate was 4.1/100,000 inhabitant-years. Against this baseline, two clusters were identified: the first, of increased risk (RR = 1.66), comprising 18 districts in the central region; the second, of decreased risk (RR = 0.78), including 14 districts in the southern region. The downtown area toward the southwestern region of the city displayed the highest risk for suicide, and though the overall risk may be considered low, the rate climbs up to an intermediate level in this region. One logistic regression analysis contrasted the risk cluster (18 districts) against the other remaining 78 districts, testing the effects of socioeconomic-cultural variables. The following categories of proportion of persons within the clusters were identified as risk factors: singles (OR = 2.36), migrants (OR = 1.50), Catholics (OR = 1.37) and higher income (OR = 1.06). In a second logistic model, likewise conceived, the following categories of proportion of persons were identified as protective factors: married (OR = 0.49) and Evangelical (OR = 0.60). Conclusions: This risk/ protection profile is in accordance with the interpretation that, as a social phenomenon, suicide is related to social isolation. Thus, the classical framework put forward by Durkheim seems to still hold, even though its categorical expression requires re-interpretation.

Inequalities in mortality of men by oral and pharyngeal cancer in Barcelona, Spain and São Paulo, Brazil, 1995–2003

Abstract Background Large inequalities of mortality by most cancers in general, by mouth and pharynx cancer in particular, have been associated to behaviour and geopolitical factors. The assessment of socioeconomic covariates of cancer mortality may be relevant to a full comprehension of distal determinants of the disease, and to appraise opportune interventions. The objective of this study was to compare socioeconomic inequalities in male mortality by oral and pharyngeal cancer in two major cities of Europe and South America. Methods The official system of information on mortality provided data on deaths in each city; general censuses informed population data. Age-adjusted death rates by oral and pharyngeal cancer for men were independently assessed for neighbourhoods of Barcelona, Spain, and São Paulo, Brazil, from 1995 to 2003. Uniform methodological criteria instructed the comparative assessment of magnitude, trends and spatial distribution of mortality. General linear models assessed ecologic correlations between death rates and socioeconomic indices (unemployment, schooling levels and the human development index) at the inner-city area level. Results obtained for each city were subsequently compared. Results Mortality of men by oral and pharyngeal cancer ranked higher in Barcelona (9.45 yearly deaths per 100,000 male inhabitants) than in Spain and Europe as a whole; rates were on decrease. São Paulo presented a poorer profile, with higher magnitude (11.86) and stationary trend. The appraisal of ecologic correlations indicated an unequal and inequitably distributed burden of disease in both cities, with poorer areas tending to present higher mortality. Barcelona had a larger gradient of mortality than São Paulo, indicating a higher inequality of cancer deaths across its neighbourhoods. Conclusion The quantitative monitoring of inequalities in health may contribute to the formulation of redistributive policies aimed at the concurrent promotion of wellbeing and social justice. The assessment of groups experiencing a higher burden of disease can instruct health services to provide additional resources for expanding preventive actions and facilities aimed at early diagnosis, standardized treatments and rehabilitation.

The impact of atmospheric particulate matter on cancer incidence and mortality in the city of São Paulo, Brazil

This study aimed to verify the impact of inhalable particulate matter (PM10) on cancer incidence and mortality in the city of São Paulo, Brazil. Statistical techniques were used to investigate the relationship between PM10 on cancer incidence and mortality in selected districts. For some types of cancer (skin, lung, thyroid, larynx, and bladder) and some periods, the correlation coefficients ranged from 0.60 to 0.80 for incidence. Lung cancer mortality showed more correlations during the overall period. Spatial analysis showed that districts distant from the city center showed higher than expected relative risk, depending on the type of cancer. According to the study, urban PM10 can contribute to increased incidence of some cancers and may also contribute to increased cancer mortality. The results highlight the need to adopt measures to reduce atmospheric PM10 levels and the importance of their continuous monitoring.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

Spatial and temporal variation in settlement, growth and condition of the rockfish species Sebastes caurinus and Sebastes carnatus in the Channel Islands region, Santa Barbara, CA

Survival during the early life stages of marine species, including nearshore temperate reef fishes, is typically very low, and small changes in mortality rates, due to physiological and environmental conditions, can have marked effects on survival of a cohort and, on a larger scale, on the success of a recruitment season. Moreover, trade offs between larval growth and accumulation of energetic resources prior to settlement are likely to influence growth and survival until this critical period and afterwards. Rockfish recruitment rates are notoriously variable between years and across geographic locations. Monitoring of rates of onshore delivery of pelagic juveniles (defined here as settlement) of two species of nearshore rockfishes, Sebastes caurinus and Sebastes carnatus, was done between 2003-2009 years using artificial collectors placed at San Miguel and Santa Cruz Island, off Southern California coast. I investigated spatiotemporal variation in settlement rate, lipid content, pelagic larval duration and larval growth of the newly settled fishes; I assessed relationships between birth date, larval growth, early life-history characteristics and lipid content at settlement, considering also interspecific differences; finally, I attempt to relate interannual patterns of settlement and of early life history traits to easily accessible, local and regional indices of ocean conditions including in situ ocean temperature and regional upwelling, sea surface temperature (SST) and Chlorophyll-a (Chl-a) concentration. Spatial variations appeared to be of low relevance, while significant interannual differences were detected in settlement rate, pelagic larval duration and larval growth. The amount of lipid content of the newly settled fishes was highly variable in space and time, but did not differ between the two species and did not show any relationships with early life history traits, indicating that no trade off involved these physiological processes or they were masked by high individual variability in different periods of larval life. Significant interspecific differences were found in the timing of parturition and settlement and in larval growth rates, with S. carnatus growing faster and breeding and settling later than S. caurinus. The two species exhibited also different patterns of correlations between larval growth rates and larval duration. S. carnatus larval duration was longer when the growth in the first two weeks post-hatch was faster, while S. caurinus had a shorter larval duration when grew fast in the middle and in the end of larval life, suggesting different larval strategies. Fishes with longer larval durations were longer in size at settlement and exhibited longer planktonic phase in periods of favourable environmental conditions. Ocean conditions had a low explanatory power for interannual variation in early life history traits, but a very high explanatory power for settlement fluctuations, with regional upwelling strength being the principal indicator. Nonetheless, interannual variability in larval duration and growth were related to great phenological changes in upwelling happened during the period of this study and that caused negative consequences at all trophic levels along the California coast. Despite the low explanatory power of the environmental variables used in this study on the variation of larval biological traits, environmental processes were differently related with early life history characteristics analyzed to species, indicating possible species-specific susceptibility to ocean conditions and local environmental adaptation, which should be further investigated. These results have implications for understanding the processes influencing larval and juvenile survival, and consequently recruitment variability, which may be dependent on biological characteristics and environmental conditions.

The effects of hypocalcemia on spatial alternans and ventricular fibrillation studied with the optical mapping technique

The heart is a wonderful but complex organ: it uses electrochemical mechanisms in order to produce mechanical energy to pump the blood throughout the body and allow the life of humans and animals. This organ can be subject to several diseases and sudden cardiac death (SCD) is the most catastrophic manifestation of these diseases, responsible for the death of a large number of people throughout the world. It is estimated that 325000 Americans annually die for SCD. SCD most commonly occurs as a result of reentrant tachyarrhythmias (ventricular tachycardia (VT) and ventricular fibrillation (VF)) and the identification of those patients at higher risk for the development of SCD has been a difficult clinical challenge. Nowadays, a particular electrocardiogram (ECG) abnormality, “T-wave alternans” (TWA), is considered a precursor of lethal cardiac arrhythmias and sudden death, a sensitive indicator of risk for SCD. TWA is defined as a beat-to-beat alternation in the shape, amplitude, or timing of the T-wave on the ECG, indicative of the underlying repolarization of cardiac cells [5]. In other words TWA is the macroscopic effect of subcellular and celluar mechanisms involving ionic kinetics and the consequent depolarization and repolarization of the myocytes. Experimental activities have shown that TWA on the ECG is a manifestation of an underlying alternation of long and short action potential durations (APDs), the so called APD-alternans, of cardiac myocytes in the myocardium. Understanding the mechanism of APDs-alternans is the first step for preventing them to occur. In order to investigate these mechanisms it’s very important to understand that the biological systems are complex systems and their macroscopic properties arise from the nonlinear interactions among the parts. The whole is greater than the sum of the parts, and it cannot be understood only by studying the single parts. In this sense the heart is a complex nonlinear system and its way of working follows nonlinear dynamics; alternans also, they are a manifestation of a phenomenon typical in nonlinear dynamical systems, called “period-dubling bifurcation”. Over the past decade, it has been demonstrated that electrical alternans in cardiac tissue is an important marker for the development of ventricular fibrillation and a significant predictor for mortality. It has been observed that acute exposure to low concentration of calcium does not decrease the magnitude of alternans and sustained ventricular Fibrillation (VF) is still easily induced under these condition. However with prolonged exposure to low concentration of calcium, alternans disappears, but VF is still inducible. This work is based on this observation and tries to make it clearer. The aim of this thesis is investigate the effect of hypocalcemia spatial alternans and VF doing experiments with canine hearts and perfusing them with a solution with physiological ionic concentration and with a solution with low calcium concentration (hypocalcemia); in order to investigate the so called memory effect, the experimental activity was modified during the way. The experiments were performed with the optical mapping technique, using voltage-sensitive dye, and a custom made Java code was used in post-processing. Finding the Nolasco and Dahlen’s criterion [8] inadequate for the prediction of alternans, and takin into account the experimental results, another criterion, which consider the memory effect, has been implemented. The implementation of this criterion could be the first step in the creation of a method, AP-based, discriminating who is at risk if developing VF. This work is divided into four chapters: the first is a brief presentation of the physiology of the heart; the second is a review of the major theories and discovers in the study of cardiac dynamics; the third chapter presents an overview on the experimental activity and the optical mapping technique; the forth chapter contains the presentation of the results and the conclusions.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.