Socioeconomic and demographic characterization of an endemic malaria region in Brazil by multiple correspondence analysis

Relapsing Plasmodium vivax malaria in a 12-year-old Brazilian girl: A case report

Plasmodium vivax causes the vast majority of malaria cases in Brazil. The lifecycle of this parasite includes a latent stage in the liver, the hypnozoite. Reactivation of hypnozoites induces repeated relapses. We report a case of two relapses of vivax malaria in a teenage girl after conventional treatment with chloroquine and primaquine. Chloroquine prophylactic treatment for three months was prescribed with a favourable outcome of the case.

Spatiotemporal overlapping of dengue, chikungunya, and malaria infections in children in Kenya

Malaria, chikungunya virus (CHIKV), and dengue virus (DENV) are endemic causes of fever among children in Kenya. The risks of infection are multifactorial and may be influenced by built and social environments. The high resolution overlapping of these diseases and factors affecting their spatial heterogeneity has not been investigated in Kenya. From 2014-2018, we prospectively followed a cohort of children from four communities in both coastal and western Kenya. Overall, 9.8% were CHIKV seropositive, 5.5% were DENV seropositive, and 39.1% were malaria positive (3521 children tested). The spatial analysis identified hot-spots for all three diseases in each site and in multiple years. The results of the model showed that the risk of exposure was linked to demographics with common factors for the three diseases including the presence of litter, crowded households, and higher wealth in these communities. These insights are of high importance to improve surveillance and targeted control of mosquito-borne diseases in Kenya.

Clustering patterns in polysubstance mortality in the United States in 2017: a multiple correspondence analysis of death certificate data

PURPOSE

The main goal of this analysis was to identify mortality patterns apparent when many drug classes are analyzed together.

METHODS

The Drug Involved Mortality database is a registry of drug terms mentioned on death certificates of all drug-related deaths in the United States. Means of total number of drugs involved and percentages of specific drug combinations were calculated. Dimensionality reduction using multiple correspondence analysis and hierarchical clustering identified clusters of drugs listed on death certificates.

RESULTS

An average of 2.4 specific drugs were listed on death certificates in 2017. For 9 of the top 10 drugs involved, over 80% of deaths involved at least one other drug. As expected, opioid drugs and psychostimulants clustered together, but other psychoactive substances (non-opioid analgesics, sedatives, antidepressants, antipsychotics) clustered together into multi-class groups. Other drugs (e.g., acetaminophen, oxymorphone) were frequently involved in polysubstance death, but did not cluster with any other specific drug. Deaths involving illicit drugs listed fewer drugs than deaths involving prescription drugs.

CONCLUSIONS

While individual drug substances might contribute to many deaths (e.g., fentanyl), polysubstance mortality is more common than single substance mortality. Multidimensional analyses integrating all drugs involved are useful to identify uncommon patterns of overdose and changing trends.

How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states

Dengue is a vector-borne disease present in most tropical countries, infecting an average of 50 to 100 million people per year. Socioeconomic, demographic, and environmental factors directly influence the transmission cycle of the dengue virus (DENV). In Brazil, these factors vary between regions producing different profiles of dengue transmission and challenging the epidemiological surveillance of the disease. In this article, we aimed at classifying the profiles of dengue transmission in 1,823 Brazilian municipalities, covering different climates, from 2010 to 2019. Time series data of dengue cases were obtained from six states: Ceará and Maranhão in the semiarid Northeast, Minas Gerais in the countryside, Espírito Santo and Rio de Janeiro in the tropical Atlantic coast, and Paraná in the subtropical region. To describe the time series, we proposed a set of epi-features of the magnitude and duration of the dengue epidemic cycles, totaling 13 indicators. Using these epi-features as inputs, a multivariate cluster algorithm was employed to classify the municipalities according to their dengue transmission profile. Municipalities were classified into four distinct dengue transmission profiles: persistent transmission (7.8%), epidemic (21.3%), episodic/epidemic (43.2%), and episodic transmission (27.6%). Different profiles were associated with the municipality’s population size and climate. Municipalities with higher incidence and larger populations tended to be classified as persistent transmission, suggesting the existence of critical community size. This association, however, varies depending on the state, indicating the importance of other factors. The proposed classification is useful for developing more specific and precise surveillance protocols for regions with different dengue transmission profiles, as well as more precise public policies for dengue prevention.

Dengue is one of the fastest-growing vector-borne diseases in the world. Currently, vaccines are experimental and are not very effective, so prevention depends on the control of the mosquito Aedes aegypti. Health promotion campaigns aimed at encouraging people to reduce mosquito breeding sites have limited effect. In addition, the heterogeneity of the territories that have dengue becomes a major challenge for the epidemiological surveillance of the disease. Brazil has a territory of continental size, and single standardized surveillance is not very effective for monitoring this arbovirus. Classifying types of dengue dynamics based on features of the epidemiological cycle in each location has the potential to increase the precision of surveillance and control strategies. In our study, we were able to classify areas according to different dengue transmission profiles, ranging from episodic to persistent transmission. These results can provide tools to guide actions aimed at achieving the World Health Organization’s goals of eliminating neglected tropical diseases in countries that have the virus.

Identifying Potential Factors Associated with High HIV viral load in KwaZulu-Natal, South Africa using Multiple Correspondence Analysis and Random Forest Analysis

Background

Sustainable Human Immunodeficiency Virus (HIV) virological suppression is crucial to achieving the Joint United Nations Programme of HIV/AIDS (UNAIDS) 95–95-95 treatment targets to reduce the risk of onward HIV transmission. Exploratory data analysis is an integral part of statistical analysis which aids variable selection from complex survey data for further confirmatory analysis.

Methods

In this study, we divulge participants’ epidemiological and biological factors with high HIV RNA viral load (HHVL) from an HIV Incidence Provincial Surveillance System (HIPSS) sequential cross-sectional survey between 2014 and 2015 KwaZulu-Natal, South Africa. Using multiple correspondence analysis (MCA) and random forest analysis (RFA), we analyzed the linkage between socio-demographic, behavioral, psycho-social, and biological factors associated with HHVL, defined as ≥400 copies per m/L.

Results

Out of 3956 in 2014 and 3868 in 2015, 50.1% and 41% of participants, respectively, had HHVL. MCA and RFA revealed that knowledge of HIV status, ART use, ARV dosage, current CD4 cell count, perceived risk of contracting HIV, number of lifetime HIV tests, number of lifetime sex partners, and ever diagnosed with TB were consistent potential factors identified to be associated with high HIV viral load in the 2014 and 2015 surveys. Based on MCA findings, diverse categories of variables identified with HHVL were, did not know HIV status, not on ART, on multiple dosages of ARV, with less likely perceived risk of contracting HIV and having two or more lifetime sexual partners.

Conclusion

The high proportion of individuals with HHVL suggests that the UNAIDS 95–95-95 goal of HIV viral suppression is less likely to be achieved. Based on performance and visualization evaluation, MCA was selected as the best and essential exploration tool for identifying and understanding categorical variables’ significant associations and interactions to enhance individual epidemiological understanding of high HIV viral load. When faced with complex survey data and challenges of variables selection in research, exploratory data analysis with robust graphical visualization and reliability that can reveal divers’ structures should be considered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01625-6.

Spatial and temporal variability and data bias in wastewater surveillance of SARS-CoV-2 in a sewer system

The response to disease outbreaks, such as SARS-CoV-2, can be constrained by a limited ability to measure disease prevalence early at a localized level. Wastewater based epidemiology is a powerful tool identifying disease spread from pooled community sewer networks or at influent to wastewater treatment plants. However, this approach is often not applied at a granular level that permits detection of local hot spots. This study examines the spatial patterns of SARS-CoV-2 in sewage through a spatial sampling strategy across neighborhood-scale sewershed catchments. Sampling was conducted across the Reno-Sparks metropolitan area from November to mid-December of 2020. This research utilized local spatial autocorrelation tests to identify the evolution of statistically significant neighborhood hot spots in sewershed sub-catchments that were identified to lead waves of infection, with adjacent neighborhoods observed to lag with increasing viral RNA concentrations over subsequent dates. The correlations between the sub-catchments over the sampling period were also characterized using principal component analysis. Results identified distinct time series patterns, with sewersheds in the urban center, outlying suburban areas, and outlying urbanized districts generally following unique trends over the sampling period. Several demographic parameters were identified as having important gradients across these areas, namely population density, poverty levels, household income, and age. These results provide a more strategic approach to identify disease outbreaks at the neighborhood level and characterized how sampling site selection could be designed based on the spatial and demographic characteristics of neighborhoods.

Sheep's coping style can be identified by unsupervised machine learning from unlabeled data

The objective of this study was to define coping style of sheep by using unsupervised machine learning approaches. A total of 105 Norduz sheep (age 3-5 years) were subjected to a 5-minute arena test. Agglomerative Hierarchical Clustering (HCA) was performed on scores of selected principal components retained from Principal Components Analysis (PCA) on arena behaviors to identify sheep coping style. Initially, the variables retained for the PCA were determined with Bartlett's test for sphericity and Kaiser-Meyer-Olkin (KMO) measure of sample adequacy. Seven behavioral variables with KMO values greater than 0.5 were used for final PCA: the average distance to group sheep (DTG), the average distance to stimulus (DTS), the duration of locomotion (LOC), the total number of zone boundaries crossed during the test (CRS), the total number of times that tested sheep sniffed stimulus (NSS), latency to the first sniff the stimulus (LSS), and subjective scores (SCR) scored by an observer on a scale from 1 to 5 (1: extremely calm, 5: extremely restless). The first two components, which were the only ones with an eigenvalue greater than one, accounted for 70.32% of the total variation and were used for clustering analysis. Clustering tendency showed that the scores for the first two components were suitable for clustering (Hopkins' H = 0.852). Several cluster validity indexes were used to obtain aggregated results to determine the most appropriate clustering method and number of clusters. Five different clustering methods: k-means and hierarchical clustering with Ward, average, single and complete linkage were compared. Bootstrap resampling was used to evaluate the stability of a given cluster using the Jaccard coefficient. The clustering method and number of clusters corresponding to the highest rank aggregation score from the bootstrap resampling indicate that the hierarchical clustering method with average linkage and 5 clusters is the most suggested clustering method. However, Ward's algorithm identified the strongest clustering structure for hierarchical clustering, as it had the highest agglomerative coefficient value (0.98). When both Jaccard and aggregation scores are considered together, Ward's method with 3 clusters was selected as the most appropriate method. Sheep were classified into three coping styles (CS) based on HCA results as reactive (Cluster 1, n = 71), intermediate (Cluster 2, n = 22) or proactive (Cluster 3, n = 12). Coping style had significant effect on behavioral variables, DTG, DTS, LOC, CRS and NSS (P < 0.05). The individuals that have proactive coping style had the highest mean values for the variables DTG, DTS and LOC and SCR (P < 0.0001). This indicates that proactive sheep are more active then reactive sheep. The CRS, LOC and NSS mean values were higher for intermediate sheep compared to reactive sheep (P < 0.05). The NSS values were higher for intermediate sheep compare to proactive sheep (P < 0.0001). The findings of the current study show that distinct coping styles in sheep may be identified based on behaviors recorded in an arena test. The findings also revealed that sheep's coping style can be objectively identified by unsupervised machine learning from unlabeled behavioral data.

Clinical, epidemiological aspects, and trends of Hepatitis B in Brazil from 2007 to 2018

Hepatitis B virus (HBV) infection is a concern for public health due to its high prevalence, high infectivity, morbidity, and mortality worldwide. Brazil presents a low HBV prevalence, but has considerable heterogeneity among its geographic regions. Here, we describe the epidemiological profile of HBV infection in different regions of Brazil during 2007-2018, as well as the historical trends associated with the infection. We conducted an observational, ecological time-series study using secondary data collected from the National Notifiable Diseases Information System (SINAN). Our findings suggest that HBV infection was more likely to occur in young, sexually active adults. Individuals from Northeast and Midwest regions were more likely to present acute HBV infection, while individuals from South region were more likely to present chronic HBV infection, reinforcing that specific strategies are required for each particular region. Additionally, we observed a general decreasing trend of infection starting in 2014, however there was an increasing trend of infection in men and in individuals over 40 years old. Although we observed a decreasing trend in HBV infection, active surveillance is needed to prevent HBV spread and possible epidemics, as well as encouraging the vaccination of adults, especially young adult males. Our findings can inform the conduct of large-scale observational studies to evaluate clinical, economical, and social impacts of HBV infections, leading to improved social policies. Finally, our results highlight the need to improve data quality and completeness of epidemiological data, minimizing eventual errors that can make prevention and control strategies difficult.

Ecology and larval population dynamics of the primary malaria vector Nyssorhynchus darlingi in a high transmission setting dominated by fish farming in western Amazonian Brazil

Vale do Rio Juruá in western Acre, Brazil, is a persistent malaria transmission hotspot partly due to fish farming development that was encouraged to improve local standards of living. Fish ponds can be productive breeding sites for Amazonian malaria vector species, including Nyssorhynchus darlingi, which, combined with high human density and mobility, add to the local malaria burden.This study reports entomological profile of immature and adult Ny. darlingi at three sites in Mâncio Lima, Acre, during the rainy and dry season (February to September, 2017). From 63 fishponds, 10,859 larvae were collected, including 5,512 first-instar Anophelinae larvae and 4,927 second, third and fourth-instars, of which 8.5% (n = 420) were Ny. darlingi. This species was most abundant in not-abandoned fishponds and in the presence of emerging aquatic vegetation. Seasonal analysis of immatures in urban landscapes found no significant difference in the numbers of Ny. darlingi, corresponding to equivalent population density during the rainy to dry transition period. However, in the rural landscape, significantly higher numbers of Ny. darlingi larvae were collected in August (IRR = 5.80, p = 0.037) and September (IRR = 6.62, p = 0.023) (dry season), compared to February (rainy season), suggesting important role of fishponds for vector population maintenance during the seasonal transition in this landscape type. Adult sampling detected mainly Ny. darlingi (~93%), with similar outdoor feeding behavior, but different abundance according to landscape profile: urban site 1 showed higher peaks of human biting rate in May (46 bites/person/hour), than February (4) and September (15), while rural site 3 shows similar HBR during the same sampling period (22, 24 and 21, respectively). This study contributes to a better understanding of the larvae biology of the main malaria vector in the Vale do Rio Juruá region and, ultimately will support vector control efforts.

Malaria transmission in landscapes with varying deforestation levels and timelines in the Amazon: a longitudinal spatiotemporal study

The relationship between deforestation and malaria is a spatiotemporal process of variation in Plasmodium incidence in human-dominated Amazonian rural environments. The present study aimed to assess the underlying mechanisms of malarial exposure risk at a fine scale in 5-km2 sites across the Brazilian Amazon, using field-collected data with a longitudinal spatiotemporally structured approach. Anopheline mosquitoes were sampled from 80 sites to investigate the Plasmodium infection rate in mosquito communities and to estimate the malaria exposure risk in rural landscapes. The remaining amount of forest cover (accumulated deforestation) and the deforestation timeline were estimated in each site to represent the main parameters of both the frontier malaria hypothesis and an alternate scenario, the deforestation-malaria hypothesis, proposed herein. The maximum frequency of pathogenic sites occurred at the intermediate forest cover level (50% of accumulated deforestation) at two temporal deforestation peaks, e.g., 10 and 35 years after the beginning of the organization of a settlement. The incidence density of infected anophelines in sites where the original forest cover decreased by more than 50% in the first 25 years of settlement development was at least twice as high as the incidence density calculated for the other sites studied (adjusted incidence density ratio = 2.25; 95% CI, 1.38-3.68; p = 0.001). The results of this study support the frontier malaria as a unifying hypothesis for explaining malaria emergence and for designing specific control interventions in the Brazilian Amazon.

Drivers of autochthonous and imported malaria in Spain and their relationship with meteorological variables

Since the early twentieth century, the intensity of malaria transmission has decreased sharply worldwide, although it is still an infectious disease with a yearly estimate of 228 million cases. The aim of this study was to expand our knowledge on the main drivers of malaria in Spain. In the case of autochthonous malaria, these drivers were linked to socioeconomic and hygienic and sanitary conditions, especially in rural areas due to their close proximity to the wetlands that provide an important habitat for anopheline reproduction. In the case of imported malaria, the main drivers were associated with urban areas, a high population density and international communication nodes (e.g. airports). Another relevant aspect is that the major epidemic episodes of the twentieth century were strongly influenced by war and military conflicts and overcrowding of the healthcare system due to the temporal overlap with the pandemic flu of 1918. Therefore, military conflicts and overlap with other epidemics or pandemics are considered to be drivers of malaria that can-in a temporary manner-exponentially intensify transmission of the disease. Climatic factors did not play a relevant role as drivers of malaria in Spain (at least directly). However, they did influence the seasonality of the disease and, during the epidemic outbreak of 1940-1944, the climate conditions favored or coadjuvated its spread. The results of this study provide additional knowledge on the seasonal and interannual variability of malaria that can help to develop and implement health risk control measures.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s41207-021-00245-8.

Human mobility and urban malaria risk in the main transmission hotspot of Amazonian Brazil

Malaria in the Amazon is often perceived as an exclusively rural disease, but transmission has been increasingly documented within and near urban centers. Here we explore patterns and causes of urban-to-rural mobility, which places travelers at risk of malaria in Mâncio Lima, the main malaria hotspot in northwestern Brazil. We also analyze rural-to-urban mobility caused by malaria treatment seeking, which poses an additional risk of infection to urban residents. We show that the rural localities most frequently visited by urban residents–typically farming settlements in the vicinity of the town–are those with the most intense malaria transmission and also the most frequent source localities of imported malaria cases diagnosed in the town. The most mobile urban residents are typically poor males 16 to 60-years old from multi-sited households who lack a formal job. Highly mobile residents represent a priority target for more intensive and effective malaria control interventions, that cannot be readily delivered to the entire community, in this and similar urbanized endemic settings across the Amazon.

Measuring the contribution of human mobility to malaria persistence

BACKGROUND

To achieve malaria elimination, it is important to determine the role of human mobility in parasite transmission maintenance. The Alto Juruá basin (Brazil) exhibits one of the largest vivax and falciparum malaria prevalence in the Amazon. The goal of this study was to estimate the contribution of human commutes to malaria persistence in this region, using data from an origin-destination survey.

METHODS

Data from an origin-destination survey were used to describe the intensity and motivation for commutations between rural and urban areas in two Alto Juruá basin (Brazil) municipalities, Mâncio Lima and Rodrigues Alves. The relative time-person spent in each locality per household was estimated. A logistic model was developed to estimate the effect of commuting on the probability of contracting malaria for a certain residence zone inhabitant commuting to another zone.

RESULTS

The main results suggest that the assessed population is not very mobile. A total of [Formula: see text] households reported spending over [Formula: see text] of their annual person-hour in areas within the same residence zone. Study and work were the most prevalent commuting motivations, calculated at [Formula: see text] and [Formula: see text] respectively. Spending person-hours in urban Rodrigues Alves conferred relative protection to urban Mâncio Lima residents. The opposite effect was observed for those spending time in rural areas of both municipalities.

CONCLUSION

Residence area is a stronger determinant for contracting malaria than commuting zones in the Alto Juruá region. As these municipalities are a hotspot for Plasmodium transmission, understanding the main local human fluxes is essential for planning control strategies, since the probability of contracting malaria is dependent on the transmission intensity of both the origin and the displacement area. The natural conditions for the circulation of certain pathogens, such as Plasmodium spp., combined with the Amazon human mobility pattern indicate the need for disease control perspective changes. Therefore, intersectoral public policies should become the basis for health mitigation actions.

Exposure to multiple heavy metals associate with aberrant immune homeostasis and inflammatory activation in preschool children

Heavy metals generate adverse health effects by interfering with immune homeostasis and promoting inflammation in individuals. Our objective was to explore the induction of immune and inflammatory responses by multiple heavy metals in children living in the e-waste contaminated area. A total of 147 preschool children were recruited, including 73 children from Guiyu, a typical e-waste recycling area, and 74 from a reference group. Blood levels of heavy metals, including lead (Pb), cadmium (Cd), mercury (Hg) and arsenic (As), were detected using an inductively coupled plasma mass spectrometry (ICP-MS). Immune cell counts (neutrophils, monocytes, lymphocytes) were determined by an automatic blood cell analyzer, pro-inflammatory cytokines (IL-1β, IL-6, IL-8, TNF-α) and anti-inflammatory cytokines (IL-1RA, IL-4, IL-10, IL-13) were analyzed by a Luminex 200 multiplex immunoassay instrument. Multiple correspondences and linear regression analyses were applied to investigate the relationships between heavy metal exposure and relevant parameters. Results shows Guiyu children had higher levels of Pb, Cd, Hg, As, IL-1β and IL-6, but decreased lymphocyte, IL-1RA and IL-13. Neutrophil count was positively correlated with Pb, Cd and Hg exposure. Anti-inflammatory IL-1RA concentration was negatively related with Pb, Cd, Hg and As, while pro-inflammatory IL-1β and IL-6 were positively correlated with Pb. Guiyu children may have dysregulated immune response and high inflammation risk. Exposure to Pb, Cd, Hg and As could be harmful for immune response and inflammatory regulation. Our finding of decreased IL-RA production in children exposed to Pb, Cd, Hg, and As is novel and could be an opportunity for future research.

Molecular evidence of sustained urban malaria transmission in Amazonian Brazil, 2014-2015

The relative contribution of imported vs. locally acquired infections to urban malaria burden remains largely unexplored in Latin America, the most urbanised region in the developing world. Here we use a simple molecular epidemiology framework to examine the transmission dynamics of Plasmodium vivax in Mâncio Lima, the Amazonian municipality with the highest malaria incidence rate in Brazil. We prospectively genotyped 177 P. vivax infections diagnosed in urban residents between June 2014 and July 2015 and showed that local parasites are structured into several lineages of closely related microsatellite haplotypes, with the largest genetic cluster comprising 32% of all infections. These findings are very unlikely under the hypothesis of multiple independent imports of parasite strains from the rural surroundings. Instead, the presence of an endemic near-clonal parasite lineage circulating over 13 consecutive months is consistent with a local P. vivax transmission chain in the town, with major implications for malaria elimination efforts in this and similar urban environments across the Amazon.

Malaria and fish farming in the Brazilian Amazon Region: a strengths, weaknesses, opportunities, and threats analysis

INTRODUCTION

The fish farming program in Acre is as an alternative program to generate income and employment and has promising regional, national, and international markets. While the economic importance of fish farming in the Jurua Region is clear, one must address its contribution to increase malaria transmission.

METHODS

This was a qualitative study. The answers of the 16 key informants were organized into the following: (1) the healthcare services structure; (2) conscience, perception, and behaviors; and (3) socioeconomic and political issues. Each answer was classified as weaknesses, strengths, opportunities, and threats.

RESULTS

Regarding healthcare services, the frequency of household visits was reduced, and subjects presenting with malaria symptoms were required to visit a healthcare unit to be diagnosed and treated. Regarding individual's conscience, perception, and behavior, malaria was considered an insignificant disease, and a large proportion of the population were engaged in health practices that put them at risk in contacting with malaria vectors. Regarding political and economic issues, there were economic and infrastructure barriers for the development of a productive activity, and the insufficient credit or formalization of their properties prevented their access to governmental incentives and the financial market.

CONCLUSIONS

Support to fish farmers for low-cost inputs was not observed, and appropriate knowledge regarding the impact of the absence of maintenance and abandonment of fish tanks was insufficient. Moreover, insufficient healthcare services prevented not only the treatment of individuals with malaria but also the control of this disease.

Comparison of malaria incidence rates and socioeconomic-environmental factors between the states of Acre and Rondônia: a spatio-temporal modelling study

BACKGROUND

Plasmodium falciparum malaria is a threat to public health, but Plasmodium vivax malaria is most prevalent in Latin America, where the incidence rate has been increasing since 2016, particularly in Venezuela and Brazil. The Brazilian Amazon reported 193,000 cases in 2017, which were mostly confirmed as P. vivax (~ 90%). Herein, the relationships among malaria incidence rates and the proportion of accumulated deforestation were contrasted using data from the states of Acre and Rondônia in the south-western Brazilian Amazon. The main purpose is to test the hypothesis that the observed difference in incidence rates is associated with the proportion of accumulated deforestation.

METHODS

An ecological study using spatial and temporal models for mapping and modelling malaria risk was performed. The municipalities of Acre and Rondônia were the spatial units of analysis, whereas month and year were the temporal units. The number of reported malaria cases from 2009 until 2015 were used to calculate the incidence rate per 1000 people at risk. Accumulated deforestation was calculated using publicly available satellite images. Geographically weighted regression was applied to provide a local model of the spatial heterogeneity of incidence rates. Time-series dynamic regression was applied to test the correlation of incidence rates and accumulated deforestation, adjusted by climate and socioeconomic factors.

RESULTS

The malaria incidence rate declined in Rondônia but remained stable in Acre. There was a high and positive correlation between the decline in malaria and higher proportions of accumulated deforestation in Rondônia. Geographically weighted regression showed a complex relationship. As deforestation increased, malaria incidence also increased in Acre, while as deforestation increased, malaria incidence decreased in Rondônia. Time-series dynamic regression showed a positive association between malaria incidence and precipitation and accumulated deforestation, whereas the association was negative with the human development index in the westernmost areas of Acre.

CONCLUSION

Landscape modification caused by accumulated deforestation is an important driver of malaria incidence in the Brazilian Amazon. However, this relationship is not linearly correlated because it depends on the overall proportion of the land covered by forest. For regions that are partially degraded, forest cover becomes a less representative component in the landscape, causing the abovementioned non-linear relationship. In such a scenario, accumulated deforestation can lead to a decline in malaria incidence.

Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin

Despite the recent malaria burden reduction in the Americas, focal transmission persists across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high-risk individuals and households for better targeting of regional elimination efforts. Here we analyzed 5,480 records of laboratory-confirmed clinical malaria episodes combined with demographic and socioeconomic information to identify risk factors for elevated malaria incidence in Mâncio Lima, the main urban transmission hotspot of Brazil. Overdispersed malaria count data clustered into households were fitted with random-effects zero-inflated negative binomial regression models. Random-effect predictors were used to characterize the spatial heterogeneity in malaria risk at the household level. Adult males were identified as the population stratum at greatest risk, likely due to increased occupational exposure away of the town. However, poor housing and residence in the less urbanized periphery of the town were also found to be key predictors of malaria risk, consistent with a substantial local transmission. Two thirds of the 8,878 urban residents remained uninfected after 23,975 person-years of follow-up. Importantly, we estimated that nearly 14% of them, mostly children and older adults living in the central urban hub, were free of malaria risk, being either unexposed, naturally unsusceptible, or immune to infection. We conclude that statistical modeling of routinely collected, but often neglected, malaria surveillance data can be explored to characterize drivers of transmission heterogeneity at the community level and provide evidence for the rational deployment of control interventions.

Exploring the Relevance of Green Space and Epidemic Diseases Based on Panel Data in China from 2007 to 2016

Urban green space has been proven effective in improving public health in the contemporary background of planetary urbanization. There is a growing body of literature investigating the relationship between non-communicable diseases (NCDs) and green space, whereas seldom has the correlation been explored between green space and epidemics, such as dysentery, tuberculosis, and malaria, which still threaten the worldwide situation of public health. Meanwhile, most studies explored healthy issues with the general green space, public green space, and green space coverage, respectively, among which the different relevance has been rarely explored. This study aimed to examine and compare the relevance between these three kinds of green space and incidences of the three types of epidemic diseases based on the Panel Data Model (PDM) with the time series data of 31 Chinese provinces from 2007 to 2016. The results indicated that there exists different, or even opposite, relevance between various kinds of green space and epidemic diseases, which might be associated with the process of urban sprawl in rapid urbanization in China. This paper provides a reference for re-thinking the indices of green space in building healthier and greener cities.

Environmental and socioeconomic analysis of malaria transmission in the Brazilian Amazon, 2010-2015

OBJECTIVE

To analyze the environmental and socioeconomic risk factors of malaria transmission at municipality level, from 2010 to 2015, in the Brazilian Amazon.

METHODS

The municipalities were stratified into high, moderate, and low transmission based on the annual parasite incidence. A multinomial logistic regression that compared low with medium transmission and low with high transmission was performed. For each category, three models were analyzed: one only with socioeconomic risk factors (Gini index, illiteracy, number of mines and indigenous areas); a second with the environmental factors (forest coverage and length of the wet season); and a third with all covariates (full model).

RESULTS

The full model showed the best performance. The most important risks factors for high transmission were Gini index, length of the wet season and illiteracy, OR 2.06 (95%CI 1.19–3.56), 1.73 (95%CI 1.19–2.51) and 1.10 (95%CI 1.03–1.17), respectively. The medium transmission showed a weaker influence of the risk factors, being illiteracy, forest coverage and indigenous areas statistically significant but with marginal influence.

CONCLUSIONS

As a disease of poverty, the reduction in wealth inequalities and, therefore, health inequalities, could reduce the transmission considerably. Besides, environmental risk factors as length of the wet season should be considered in the planning, prevention and control. Municipality-level and fine-scale analysis should be done together to improve the knowledge of the local dynamics of transmission.

Spatial spread of malaria and economic frontier expansion in the Brazilian Amazon

The temporal and spatial evolution of malaria was described for the postfrontier phase of the Brazilian Amazon in 2003–2013. The current ecological study aimed to understand the relationship between spatial population mobility and the distribution of malaria cases. The study identified epidemiologically relevant areas using regional statistical modeling and spatial analyses that considered differential infections and types of work activities. Annual parasite incidence (API) in the region was highest in hotspots along the Amazon River and in the south and west settlement zone of Hiléia, with concentrations in environmental protection areas and açaí and Brazil nut extraction areas. The dispersal force decreased in the Central Amazon due to rapid urbanization and improved socioeconomic conditions for workers in consolidated settlement areas. The study characterized the spatial patterns of disease transmission according to the economic activity and regionalization of geographic areas, confirming that the incidence of infection by work activity and labor flow is linked to extractive activities and agricultural settlements.

Structural characterization of piglet producing farms and their sow removal patterns in Finland

Background

The main objectives of this observational, cross-sectional study were to characterize piglet producing farms in Finland and to investigate how farm profiles are associated with sow culling and mortality.The study was conducted on 43 farms during 2014. A questionnaire survey was administered in-person and supplemented with observations in the housing facilities. Annual removal figures and average monthly sow inventories were retrieved from a centralized animal data recording system (National Swine Registry) administered by the Finnish Food Authority. Multiple correspondence analysis and hierarchical clustering were used to explore the complex underlying data-driven patterns.

Results

Sow removal varied markedly between farms with an overall average culling percentage of 38.0% (95% CI 34.1-42.0) and a relatively high average mortality percentage 9.7% (95% CI 7.9-11.5). We identified three farm clusters, which differed both in their typologies and removal patterns. Cluster 1 included farms with features indicative of a semi-intensive or intensive kind of farming, such as larger herd and room sizes, higher stocking density and more sows per caretaker. Most of the cluster 1 farms exceeded the investigated cut-off levels for culling and mortality. Cluster 2 farms were estimated to have the best animal welfare among the sample farms based on a combination of environmental indicators (e.g. amount of bedding, rooting and nesting materials, space allowance, pen cleanliness) and the lowest level of sow mortality as an animal-based indicator. Cluster 3 farms followed a strategy of a rather non-intensified system based on the predominance of smaller herd size, lower stocking density and less sows per caretaker, combined breeding and gestation rooms and rare use of farrowing induction. This cluster showed the lowest culling levels within the sample.

Conclusions

This study captures the diversity among Finnish sow farms and provides a baseline assessment of their practices and facilities. Our results support the notion that farm typologies are associated with sow culling and mortality. In summary, the control of suboptimal sow removal cannot be based on single improvements only, because of other limitations within the individual farm resources.

The Urban Gradient in Malaria-Endemic Municipalities in Acre: Revisiting the Role of Locality

Urbanization has altered the distribution of diseases of public health importance along gradients of human occupation. Adopting dichotomous urban/rural categories to explain differences in the risk of exposure, as well as the prevention of diseases is insufficient. In this paper, we present the potential of representations based on the gradient perspective to characterize the living spaces of municipalities where malaria is endemic in northwest Acre. Inventoried data in 40 localities in the Mâncio Lima and Rodrigues Alves municipalities and information on land use and land cover obtained from the TerraClass Database were used to characterize the urban spatial forms and their social content. Results showed a gradient of intensities: from municipal seats to the most connected localities through the road network to riverine communities. Based on the results, we hope to advance the discussion about the use of normative definitions of “urban” and “rural” for public policies and actions to control and eliminate malaria, considering the position of each locality in its own locally referenced urban gradient.

Abundance of impacted forest patches less than 5 km2 is a key driver of the incidence of malaria in Amazonian Brazil

The precise role that deforestation for agricultural settlements and commercial forest products plays in promoting or inhibiting malaria incidence in Amazonian Brazil is controversial. Using publically available databases, we analyzed temporal malaria incidence (2009–2015) in municipalities of nine Amazonian states in relation to ecologically defined variables: (i) deforestation (rate of forest clearing over time); (ii) degraded forest (degree of human disturbance and openness of forest canopy for logging) and (iii) impacted forest (sum of deforested and degraded forest patches). We found that areas affected by one kilometer square of deforestation produced 27 new malaria cases (r² = 0.78; F1,10 = 35.81; P < 0.001). Unexpectedly, we found both a highly significant positive correlation between number of impacted forest patches less than 5 km² and malaria cases, and that these patch sizes accounted for greater than ~95% of all patches in the study area. There was a significantly negative correlation between extraction forestry economic indices and malaria cases. Our results emphasize not only that deforestation promotes malaria incidence, but also that it directly or indirectly results in a low Human Development Index, and favors environmental conditions that promote malaria vector proliferation.

Analyzing the Local Epidemiological Profile of Malaria Transmission in the Brazilian Amazon Between 2010 and 2015

Introduction:

Malaria still is a public health problem in the Americas. In 2015, Brazil accounted for 37% of all cases in the Americas, and of these cases, 99.5% were located in the Brazilian Amazon. Despite the mobilization of resources from the Brazilian National Plan for Malaria Control, too many municipalities have high transmission levels. The objective of this study is to evaluate the local epidemiological profile of malaria and its trend between 2010 and 2015 in the Brazilian Amazon. This study also aims to recognize the epidemiological differences in the local temporo-spatial dynamics of malaria.

Methods:

Malaria data were stratified by the annual parasite incidence (API) over the six-year period and by municipality. We used the method of seasonal decomposition by Loess smoothing to capture trend, seasonal and irregular components. A generalized linear model was applied to quantify trends, and the Kruskal-Wallis Rank Sum was applied to test for seasonality significance.

Results:

The malaria API declined by 61% from 2010 to 2015, and there was a 40% reduction of municipalities with high transmission (determined as an API higher than 50). In 2015, 9.4% of municipalities had high transmission and included 62.8% of the total cases. The time-series analyses showed different incidence patterns by region after 2012; several states have minimized the effect of the seasonality in their incidence rates, thus achieving low rates of incidence. There were 13 municipalities with sustained high transmission that have become the principal focus of malaria control; these municipalities contained 40% of the cases between 2013 and 2015.

Discussion:

Brazil has achieved advances, but more sustained efforts are necessary to contain malaria resurgence. The use of malaria stratification has been demonstrated as a relevant tool to plan malaria programs more efficiently, and spatiotemporal analysis corroborates the idea that implementing any intervention in malaria should be stratified by time to interpret tendencies and by space to understand the local dynamics of the disease.

Prevalence and risk factors for prehypertension and hypertension among adults in Central China from 2000-2011

BACKGROUND

Hypertension is frequently studied in surveys; however, prehypertension, a new blood pressure status between normotension and hypertension, is rarely reported.

METHODS

All data were derived from the China Health and Nutrition Survey (CHNS) and were analysed by logistic regression for correlation.

RESULTS

The prehypertension prevalence was 27.4%, with a hypertension rate of 36.9%. The awareness, treatment, and uncontrolled rates among all hypertension participates were 19.8%, 83.6%, and 55.0%, respectively. The epidemic rate of hypertension increased with increasing age (p < 0.001), and prehypertension appeared to have an epidemic peak in the age group of 38-57 years (p < 0.001). In general, the incidence of hypertension in urban participants was higher than in rural subjects (p < 0.001), and prehypertension in urban subjects was lower than that in rural subjects (p < 0.001). According to the results of logistic regression, hypertension and prehypertension were associated with age, gender, location, body mass index (BMI), body fat rate (BFR), waist circumference (WC), education, and the intake of energy-yielding nutrients<0.05).

CONCLUSION

The current study reveals a high epidemic rate of hypertension and prehypertension in Central China. These results indicate the urgent need to develop strategies to improve the prevention of hypertension and prehypertension in Central China.