Spatial Scan Research Articles

An innovative structural health assessment tool for existing precast concrete buildings using deep learning methods and thermal infrared satellite imagery

Currently, there is a limited number of tools that can be used to assess progressive damage of buildings in large-scale study areas. The effectiveness of such tools is also constrained by a lack of sufficient and reliable data from the buildings and the area itself. This research article presents an innovative framework for damage detection and classification of precast concrete (PC) buildings based on satellite infrared (IR) imagery. The framework uses heat leakage changes over time to assess the progressive damage of buildings. Multispectral satellite images are used for a spatial scanning and large-scale assessment of a study area. A deep learning object detection algorithm coupled with two pixel intensities classification approaches are utilized in the framework. The proposed framework is demonstrated on two case study areas (parts of Karaganda and Almaty cities) in Kazakhstan using a set of multitemporal satellite images. Overall, the proposed framework, in combination with a YOLOv3 algorithm, successfully detects 85% of the PC buildings in the study areas. The use of a peak heat leakage classification approach (in comparison to mean heat leakage classification) over the 4 years showed a good agreement with the proposed framework. On-site visual inspections confirmed that PC buildings that were classified as having “High damage probability” have indeed evident signs of deterioration, as well as a more heat leakage than the rest of the buildings in the study areas. Whilst the framework has some limitations such as its applicability to extreme continental climate and its low sensitivity to detect minor damage, the proposed innovative framework showed very promising results at detecting progressive damage in PC buildings. This article contributes towards developing more efficient long-term damage assessment tools for existing buildings in large urban areas.

Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging.

Multiphoton microscopy is a formidable tool for the pathological analysis of tumors. The physical limitations of imaging systems and the low efficiencies inherent in nonlinear processes have prevented the simultaneous achievement of high imaging speed and high resolution. We demonstrate a self-alignment dual-attention-guided residual-in-residual generative adversarial network trained with various multiphoton images. The network enhances image contrast and spatial resolution, suppresses noise, and scanning fringe artifacts, and eliminates the mutual exclusion between field of view, image quality, and imaging speed. The network may be integrated into commercial microscopes for large-scale, high-resolution, and low photobleaching studies of tumor environments.

Borehole azimuthal acoustic imaging using 3D spatial scanning: Application in acoustic detection of nearby wells

At present, it is difficult to image small-scale abnormal geo-bodies near wells using borehole acoustic imaging, as information from scattered waves is neglected and that from reflected waves is mainly used, thus resulting in low imaging resolution. Imaging methods based on scattered waves can help obtain higher-resolution measurements. Herein, a 3D scattered wave spatial scanning imaging method is proposed to make full use of multi-mode scattered waves for imaging small-scale abnormal geo-bodies near the well. The 3D finite-difference time-domain method was used to simulate the acoustic fields for borehole azimuthal acoustic imaging with a fluid-filled target borehole near a measurement well, and the imaging method was applied for the acoustic detection of nearby wells based on forward modeling and field measurement waveform data. The results show that for the fluid-filled target borehole that is approximately parallel to and distant from the measurement well, the amplitude of the scattered PP-wave is the largest followed by the mode converted PS- and SP-wave; and the amplitude of the scattered SS-wave is the smallest, which is related to the radiation, scattering, and reception of the monopole acoustic field. In this case, the scattered wave from the target borehole can be regarded as a plane-wave. The spatial scanning imaging method based on single-mode scattered acoustic waves and the 3D plane-wave imaging method provide similar imaging results. The comprehensive use of multi-mode scattered acoustic waves can further improve the imaging signal-to-noise ratio and resolution. A field example was used to verify the correctness of the forward analysis and the effectiveness of the imaging method. This study will help improve the imaging resolution for the acoustic detection of nearby wells and the evaluation of downhole hydraulic fracturing.

The time course of Visual Foraging in the lifespan: Spatial Scanning, Organization Search, and Target Processing

The time course of Visual Foraging in the lifespan: Spatial Scanning, Organization Search, and Target Processing

Revisiting the Geographical Distribution of Thyroid Cancer Incidence in Fukushima Prefecture: Analysis of Data From the Second- and Third-round Thyroid Ultrasound Examination.

After the first-round (Preliminary Baseline Survey) ultrasound-based examination for thyroid cancer in response to the accident at the Fukushima Daiichi Nuclear Power Plant in 2011, two rounds of surveys (Full-scale Survey) have been carried out in Fukushima Prefecture. Using the data from these surveys, the geographical distribution of thyroid cancer incidence over 6 or 7 years after the disaster was examined. Children and adolescents who underwent the ultrasound-based examinations in the second- and/or third-round (Full-scale) survey in addition to the first-round survey were included. With a discrete survival model, we computed age, sex, and body mass index standardized incidence ratios (SIRs) for municipalities. Then, we employed spatial statistics to assess geographic clustering tendency in SIRs and Poisson regression to assess the association of SIRs with the municipal average absorbed dose to the thyroid gland at the 59-municipality level. Throughout the second- and third-round surveys, 99 thyroid cancer cases were diagnosed in the study population of 252,502 individuals. Both flexibly shaped spatial scan statistics and maximized excess events test did not detect statistically significant spatial clustering (P = 0.17 and 0.54, respectively). Poisson regression showed no significant dose-response relationship: the estimated relative risks of lowest, middle-low, middle-high, and highest areas were 1.16 (95% confidence interval [CI], 0.52-2.59), 0.55 (95% CI, 0.31-0.97), 1.05 (95% CI, 0.79-1.40), and 1.24 (95% CI, 0.89-1.74). There was no statistical support for geographic clustering or regional association with radiation dose measures of the thyroid cancer incidence in the cohort followed up to the third-round survey (fiscal years 2016-2017) in Fukushima Prefecture.

Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.

Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis and treatment of CAD. Constrained by Nyquist theorem, dense sampling in IVOCT attains high resolving power to delineate cellular structures/features. There is a trade-off between high spatial resolution and fast scanning rate for coronary imaging. In this paper, we propose a viable spectral-spatial acquisition method that down-scales the sampling process in both spectral and spatial domain while maintaining high quality in image reconstruction. The down-scaling schedule boosts data acquisition speed without any hardware modifications. Additionally, we propose a unified multi-scale reconstruction framework, namely Multiscale-Spectral-Spatial-Magnification Network (MSSMN), to resolve highly down-scaled (compressed) OCT images with flexible magnification factors. We incorporate the proposed methods into Spectral Domain OCT (SD-OCT) imaging of human coronary samples with clinical features such as stent and calcified lesions. Our experimental results demonstrate that spectral-spatial down-scaled data can be better reconstructed than data that are down-scaled solely in either spectral or spatial domain. Moreover, we observe better reconstruction performance using MSSMN than using existing reconstruction methods. Our acquisition method and multi-scale reconstruction framework, in combination, may allow faster SD-OCT inspection with high resolution during coronary intervention.

Spatial clustering of codeine use and its association with depression: a geospatial analysis of nationally representative South African data

• We spatially identified geographical clusters of codeine use in South Africa, and investigated onset of depression overtime among depression-free individuals in communities with high concentration of codeine use. • The clusters of codeine use were found to be concentrated in the northern parts of South Africa. • Residing in a community with high concentration codeine use was associated with higher subsequent depression incidence. • Whilst opioid crisis has been believed to be epidemic in the global north particularly USA, it is also taking place in sub-Saharan Africa. There is an alarming trend in sub-Saharan Africa in the use of codeine-containing pharmaceuticals, but its risk of common comorbidities, such as mental health, remains unquantified at a national-level. We investigated the relationship between codeine use and onset of depression in South Africa at a population-level. We used nationally representative panel data from the South Africa National Income Dynamic Study to investigate the relationship between exposure to codeine use in the community (i.e. residing in a codeine hotspot) and onset of depression. Geographical hotspots of codeine use were identified using Kulldorff spatial scan statistic in SaTScan. We quantified depression onset at Wave 5 (year 2017) between individuals residing inside and outside a codeine hotspot who were depression-free at enrolment (Wave 4: 2015) using generalised estimating equation (GEE) regression models. We identified four statistically significant hotspots of codeine use, mostly located at the northern part of the country. Among 13,020 participants who were depression-free at enrolment, residing within a codeine use hotspot was significantly associated with higher subsequent onset of depression (aRR=1.21, 95% CI:1.08-1.44). Data on diagnosis of depressive disorder were not available. South Africa, a resource scarce nation with chronically limited mental health services, is not spared from the global opioid epidemic and its impact on depression. Targeted scale-up access to agonist therapy to effectively treat (opioid) addiction in communities at risk for high exposure to codeine use could reduce the risk of subsequent mental health challenges.

Design of Monolithic 2D Optical Phased Arrays Heterogeneously Integrated with On-Chip Laser Arrays Based on SOI Photonic Platform.

In this work, heterogeneous integration of both two-dimensional (2D) optical phased arrays (OPAs) and on-chip laser arrays based on a silicon photonic platform is proposed. The tunable multi-quantum-well (MQW) laser arrays, active switching/shifting arrays, and grating antenna arrays are used in the OPA module to realize 2D spatial beam scanning. The 2D OPA chip is composed of four main parts: (1) tunable MQW laser array emitting light signals in the range of 1480-1600 nm wavelengths; (2) electro-optic (EO) switch array for selecting the desired signal light from the on-chip laser array; (3) EO phase-shifter array for holding a fixed phase difference for the uniform amplitude of specific optical signal; and (4) Bragg waveguide grating antenna array for controlling beamforming. By optimizing the overall performances of the 2D OPA chip, a large steering range of 88.4° × 18° is realized by tuning both the phase and the wavelength for each antenna. In contrast to the traditional thermo-optic LIDAR chip with an external light source, the overall footprint of the 2D OPA chip can be limited to 8 mm × 3 mm, and the modulation rate can be 2.5 ps. The ultra-compact 2D OPA assembling with on-chip tunable laser arrays using hybrid integration could result in the application of a high-density, high-speed, and high-precision lidar system in the future.

Spatial variability of mother-to-child human immunodeficiency virus transmission in a province in the Brazilian Rainforest: An ecological study.

The mother-to-child transmission (MTCT) of the human immunodeficiency virus (HIV) remains a serious public health problem in the Brazilian Rainforest. This study aimed to spatially analyze this type of infection between 2007 and 2018 in Pará, which is the second-largest Brazilian state in the Brazilian Rainforest and also has the highest MTCT of HIV in Brazil. We analyzed the incidence rates of HIV (including the acquired immunodeficiency syndrome (AIDS) by MTCT as the main route of infection in children younger than 13 years old and whose mothers live in Pará. We employed spatial autocorrelation, spatial scanning, and geographic-weighted spatial regression techniques. In the period of this study, 389 new HIV/AIDS were noted, with territorial expansion of the incidence rates in the municipalities in northern and southern Pará having the highest rates. São Francisco do Pará had high spatial risk and high-spatiotemporal risk clusters comprising municipalities in western and south-western Pará between 2013 and 2016. The spatial variability of HIV/AIDS incidence rates was found to be common in the number of men and women with formal jobs; unemployed ≥18 years old people; elementary school pupils; and families enrolled in the "Single Registry for Social Programs". The social equity approach in Pará guarantee pregnant women access to preventive, diagnostic and treatment health services and their children should be supported to eliminate the MTCT of HIV in Pará.

Time-resolved photoconductivity distribution measurement by a synchronized double-scanning method.

The lifetime and the distribution of photoconductivity generated in laser-illuminated semiconductors are critical to photoconductivity-based applications. We propose a synchronized double-scanning method to measure time-resolved diffusion in the form of an afterglow embedded in the distribution map. The method combines spatial scanning of a coaxial resonator with synchronized laser scanning to map the dynamically excited conductivity on a semiconductor wafer. Thus, the photoconductivity afterglow effects can be mapped and retrieved by images of dynamic photoconductivity distribution. The photoconductivity lifetimes of silicon wafers with different thicknesses and by different lasers were measured and evaluated, which were also validated by the microwave photoconductivity decay (μ-PCD) method. In addition, the behavior of photoconductivity diffusion around a structural defect was exhibited. The method is nondestructive and can be applied in the photoconductivity property diagnostic.

Numerical simulation of borehole 3D scanning acoustic imaging using scattered waves

Oil and gas exploration increasingly requires high-resolution imaging of small, irregularly shaped, and highly heterogeneous well-side complex and abnormal geo-bodies. Conventional borehole acoustic imaging is often unable to accurately obtain the position and azimuth of small-scale abnormal geo-bodies. This study presents an inversion method that uses scattered waves for borehole 3D acoustic imaging and an implementation scheme that combines plane and spherical scanning imaging. The finite-difference time-domain method was used to simulate the acoustic fields for borehole azimuthal acoustic imaging of one and two caves next to a well. The proposed inversion method of 3D spatial scanning based on multi-mode wave information was validated through numerical simulations investigating the effect of different parameters on the imaging results. The simulation results show that the cave-scattered waves include the PP-, PS-, SP-, and SS-waves. When plane scanning imaging is performed based on a single wave mode, the other wave modes become interference factors. After the weighted processing of the PP-, PS-, SP-, and SS-waves, plane scanning imaging based on multi-mode scattered acoustic waves is shown to weaken pseudo-solutions, enhance the signal-to-noise ratio, and improve the radial and axial positioning accuracy of scatterers. When the scatterer is close to the borehole axis, the echo received by the receiver is not a real plane wave. In contrast with the 3D slowness time coherence (STC) and beamforming methods, spherical scanning imaging based on single-mode scattered acoustic waves completely considers this fact, which improves its azimuth positioning accuracy. Furthermore, spherical scanning imaging based on multi-mode scattered acoustic waves accurately estimates the azimuth of caves beside a well with a high imaging resolution. Finally, numerical simulation results were validated using the field measurement data of a well, and the actual imaging effect of the new method was tested. Therefore, rather than using single-mode reflected waves with limited information, the proposed method of scanning imaging using scattered acoustic waves can substantially improve the imaging resolution and positioning accuracy of small-scale abnormal geo-bodies beside a well and enhance the detection range.

Identifying hidden Zika hotspots in Pernambuco, Brazil: a spatial analysis.

Northeast Brazil has the world's highest rate of Zika-related microcephaly. However, Zika case counts cannot accurately describe burden because mandatory reporting was only established when the epidemic was declining in the region. To advance the study of the Zika epidemic, we identified hotspots of Zika in Pernambuco state, Northeast Brazil, using Aedes-borne diseases (dengue, chikungunya and Zika) and microcephaly data. We used Kulldorff's Poisson purely spatial scan statistic to detect low- and high-risk clusters for Aedes-borne diseases (2014-2017) and for microcephaly (2015-2017), separately. Municipalities were classified according to a proposed gradient of Zika burden during the epidemic, based on the combination of cluster status in each analysis and considering the strength of the evidence. We identified 26 Aedes-borne diseases clusters (11 high-risk) and 5 microcephaly clusters (3 high-risk) in Pernambuco. According to the proposed Zika burden gradient, our results indicate that the northeast of Pernambuco and the Sertão region were hit hardest by the Zika epidemic. The first is the most populous area of Pernambuco, while the second has one of the highest rates of social and economic inequality in Brazil. We successfully identified possible hidden Zika hotspots using a simple methodology combining Aedes-borne diseases and microcephaly information.

Geographical weighted regression analysis of delayed antenatal care initiation and its factors among all reproductive-aged women in Ethiopia, 2016

BackgroundDelayed antenatal care is when the first visit is carried out after 12 gestational weeks. Despite the fact that many studies have been conducted on antenatal care initiation, little attention has been paid to its spatial pattern. Therefore, this study examine geographical weighted regression analysis of delayed antenatal care initiation and its factors among all reproductive-aged women in Ethiopia.ObjectiveTo assess geographical weighted regression analysis of delayed antenatal care initiation and its factors among all reproductive-aged women in Ethiopia, 2016.MethodsThis study was grounded on the 2016 Ethiopian Demographic Health Survey. It incorporated extracted sample size of 4740 (weighted) reproductive-aged women. ArcGIS version 10.8 and SaTScan™ version 9.7 software were employed to investigate geographic information. To distinguish factors associated with hotspot areas, local and global models were fitted.Resultthe geographic pattern of Delayed antenatal care initiation was clustered (Moran’s I = 0.38, p < 0.001). Kuldorff’s spatial scan statistics discovered three significant clusters. The most likely cluster (LLR = 66.13, p < 0.001) was situated at the zones of SNNP and Oromia regions. In the local model, being uneducated, being poor wealth, having an unwanted pregnancy, and having higher birth order were factors associated with spatial variation of delayed antenatal care.ConclusionThe spatial pattern of delayed antenatal care in Ethiopia is clustered. Maternal education, wealth status, pregnancy desirability, and birth order were predictor variables of spatial variation of delayed antenatal care. Therefore, designing a hotspot area-based interventional plan could help to improve early ANC initiation.

Spatial distribution, determinants and trends of full vaccination coverage in children aged 12–59 months in Peru: A subanalysis of the Peruvian Demographic and Health Survey

ObjectiveTo assess the spatial distribution, trends and determinants of crude full vaccination coverage (FVC) in children aged 12–59 months between 2010 and 2019 in Peru.Design, setting and analysisA cross-sectional study...

Syndemics of intimate partner violence among women in HIV endemic South Africa: geospatial analysis of nationally representative data

Despite some improvement in lowering HIV incidence, HIV-related challenges, such as intimate partner violence (IPV), remain unacceptably high among women in South Africa. For decades, researchers and activists have pointed to the complex and intertwined reality of the substance abuse, violence and AIDS (SAVA) syndemic that endangers women. However, more recent systematic review/meta-analysis evidence points to inconclusive association between IPV and alcohol use. Furthermore, much of the evidence is often non-population-based that focuses on the co-occurrence rather than synergistic SAVA interaction. In this study, using the latest data from the South Africa Demographic and Health Survey (SA-DHS), we identified geographic synergistic clustering of IPV associated with HIV and substance abuse in South Africa as a measure of population-level interactions among these factors. The SA-DHS is a nationally representative sample that includes wide-ranging data on health, social challenges and household geo-locations of 5,874 women who participated in the domestic violence module. First, geographical IPV, harmful alcohol use (as the substance abuse measure available in SA-DHS) and HIV clusters were identified using the Kulldorff spatial scan statistic in SaTScan. Second, synergistic interactions related to recent IPV (i.e. recent physical, sexual, emotional violence during the last 12 months) with harmful alcohol use and HIV challenge were measured using RERI [Relative excess risk due to interaction], AP [attributable proportion] and S [Synergy index]. In our results, we spatially identified geographical physical IPV syndemic interactions in parts of the Eastern Cape/Free State Provinces (RERI = 4.42 [95% CI: 2.34–6.51], AP = 0.56 [95% CI: 0.44–0.68], S = 2.77 [95% CI: 2.01–3.84], but not in other forms of IPV. Although IPV, based on decade old concept of SAVA syndemic, was less common/widespread than expected from the national scale population-based data, we identified population-level physical violence syndemic occurring in South Africa. Our study highlights the need to prioritize public health response targeting vulnerable populations residing in these high-risk areas of syndemic mechanisms linking these synergistic epidemics that women face in South Africa.

SkyScan 1172 X-ray micro-CT scanner of well-core digital modeling for geophysical analysis of landscape polystructures

ABSTRACT The present study deals with algorithms for the acquisition of a well-core digital model that is used in the Digital Well-Core technology or “Digital Petrophysics.” The study involved the initial implementation stage of this technology: identification of geometric dimensions of a sample and spatial scanning resolution, as well as of scanning and reconstruction settings to examine a well core in a SkyScan 1172 X-ray micro-CT system. Well-core samples 30 mm wide (7 µm/pixel resolution), 10 mm wide (4 µm/pixel resolution) and 5 mm wide (1.5 µm/pixel resolution) were examined by X-ray micro-computed tomography. The porosity coefficient of all samples was measured by the water-saturation and weighing method. The digital models were used to estimate the porosity coefficient compared to the standard method. The results demonstrated that the best convergence of micro-CT and standard method data was achieved with 5-mm samples at a 1.5 µm/pixel scan resolution. A study on digital model optimization through noise reduction in the NRecon standard software was also conducted and discovered that the best convergence of porosity coefficients was attained when smoothing was set at 8. The scanning and reconstruction settings proposed for well-core samples can be used to implement the Digital Well-Core technology.

Hotspots and determinants of women’s discriminatory attitude towards people living with HIV; evidence from ethiopian demographic and health survey data

BackgroundHuman Immunodeficiency Virus (HIV) is the major public health concern in Ethiopia with more profound effect on women. Discriminatory attitude towards people living with HIV (PLWH) impose a significant impact on patient outcomes and related issues. Hence, this study aimed to investigate the hotspot areas and determinant factors of women’s discriminatory attitude towards people living with HIV.MethodsAn in-depth secondary data analysis was conducted based on Ethiopian demographic and health survey (EDHS) 2016. A total of weighed 13,822 reproductive-age women were included in the analysis. The non-spatial analysis was conducted using Stata 16. A mixed effect multi-level logistic regression model was fitted to identify determinant factors of discriminatory attitude towards PLWH. A p-value < 0.2 and 0.05 were used as a cut-off point to declare statistical significance for the bi- and multi-variable regression models, respectively. Four separate models i.e. the null, individual, community level model, and a fourth combined model were fitted. Model comparison was done using deviance. Random effect parameters such as correlation coefficient, median odds ratio, and proportional change in variance were used to explain the variation between and within clusters. Global and local level spatial analyses were conducted using Global Moran’s index, GetisOrd Gi* statistics, and Spatial scan statistics were conducted.ResultsThe magnitude of women’s discriminatory attitude towards PLWH was 62.66% (95%CI: 60.12, 65.10). The discriminatory attitude of women towards PLWH was spatially clustered (Moran’s index = 0.41, P < 0.01). The hotspots of discriminatory attitude towards PLWH were detected in most parts of the Tigray region; Northern, and southeast borders of the Amhara region; Addis Ababa city; Central, Southern, and western Oromiya region; and East, south, and northeastern parts of South Nations, Nationalities and Peoples Region (SNNPR). Being rural resident, and having no media exposure were positively associated while better educational statuses, better wealth index, unmarried, having comprehensive HIV knowledge, Orthodox religion fellow, and ever being tested for HIV were negatively associated with women’s discriminatory attitude towards people living with HIV.ConclusionDiscriminatory attitude of women towards PLWH was high in Ethiopia. Hotspots were detected in Amhara, Oromiya, SNNPR, Tigray regions, and Addis Ababa city. Socio-demographic, socio-economic, and HIV knowledge-related factors determine the women’s discriminatory attitude towards PLWH.

Spatiotemporally comparative analysis of three common infectious diseases in China during 2013–2015

BackgroundDengue fever (DF), influenza, and hand, foot, and mouth disease (HFMD) have had several various degrees of outbreaks in China since the 1900s, posing a serious threat to public health. Previous studies have found that these infectious diseases were often prevalent in the same areas and during the same periods in China.MethodsThis study combined traditional descriptive statistics and spatial scan statistic methods to analyze the spatiotemporal features of the epidemics of DF, influenza, and HFMD during 2013–2015 in mainland China at the provincial level.ResultsDF got an intensive outbreak in 2014, while influenza and HFMD were stable from 2013 to 2015. DF mostly occurred during August–November, influenza appeared during November–next March, and HFMD happened during April–November. The peaks of these diseases form a year-round sequence; Spatially, HFMD generally has a much higher incidence than influenza and DF and covers larger high-risk areas. The hotspots of influenza tend to move from North China to the southeast coast. The southeastern coastal regions are the high-incidence areas and the most significant hotspots of all three diseases.ConclusionsThis study suggested that the three diseases can form a year-round sequence in southern China, and the southeast coast of China is a particularly high-risk area for these diseases. These findings may have important implications for the local public health agency to allocate the prevention and control resources.

Epidemiological and etiological characteristics of mild hand, foot and mouth disease in children under 7 years old, Nanjing, China, 2010–2019

BackgroundMild hand, foot and mouth disease (HFMD) cases make up a relatively high proportion of HFMD while have often been overlooked. This study aimed to investigate the epidemiological and etiological characteristics of mild HFMD in Nanjing.MethodsData on mild HFMD cases, during 2010–2019 in Nanjing, were collected from the China Information System for Disease Control and Prevention. This study mainly focused on mild cases aged < 7 years. Descriptive analysis was used to summarize epidemiological and etiological characteristics of mild cases. Flexible spatial scan statistic was used to detect spatial clusters of mild cases.ResultsA total of 175,339 mild cases aged < 7 years were reported, accounting for 94.4% of all mild cases. There was a higher average annual incidence of mild HFMD in children aged < 7 years (4,428 cases/100,000) compared with children aged ≥ 7 years (14 cases/100,000, P < 0.001), and especially children aged 1-year-old (7,908 cases/100,000). Mild cases showed semi-annual peaks of activity, including a major peak (April to July) and a minor peak (September to November). The average annual incidence was higher in males (5,040 cases/100,000) than females (3,755 cases/100,000). Based on the cumulative reported cases, the most likely cluster was detected, including Yuhuatai District, Jiangning District, Jiangbei new Area, and Pukou District. The annual distribution of enterovirus serotypes showed a significant difference. During 2010–2016, Enterovirus 71 (EV71), Coxsackievirus A16 (Cox A16), and other non-EV71/Cox A16 EVs, accounted for 29.1%, 34.6%, 36.3% of all the enterovirus test positive cases, respectively. Moreover, during 2017–2019, Cox A6, Cox A16, EV71, and other non-EV71/Cox A16/Cox A6 EVs, accounted for 47.3%, 32.5%, 10.7%, 9.5%, respectively.ConclusionsChildren under 7 years old are at higher risk of mild HFMD. Regions with high risk are mainly concentrated in the areas surrounding central urban areas. Cox A16 and Cox A6 became the dominant serotypes and they alternated or were co-epidemic. Our findings could provide valuable information for improving the regional surveillance, prevention and control strategies of HFMD.

Geographical distribution and monitoring of dengue in 141 municipalities in the center-west of Brazil

In fact, it appears that dengue is characterized as a disease that has relevance to public health in the country. For the year 2019, 1,544,987 cases of dengue could be reported, with the presence of 782 confirmed deaths. Regarding the interruption of dengue epidemic cycles, it was noted that measures associated with vector control have not been successful. This study aims to analyze the spatial distribution associated with dengue cases present in the municipalities of the state of Mato Grosso, from 2015 to 2018, in order to identify the municipalities that have the highest risk rates related to the presence of arbovirus. Gross and Smoothed Rates were used through the Local Empirical Bayesian method. In order to calculate these Bayesian rates, a neighborhood matrix was developed with the presence of the continuity criterion that removed the zero risk of dengue from this calculation, thus minimizing the effects associated with the random fluctuations present in the areas that were monitored. Of course, the SaTScan software was used to calculate the Relative Risk (RR), and it was found that in this spatial scan clusters of low, medium and high risks were identified, demonstrating statistically significant data. The use of statistical techniques and spatial analysis employed in the study expanded the more detailed examination of the risk of transmission in the monitored areas, contributing significantly to the formulation and planning of integrated prevention and control strategies aimed at monitoring the arbovirus present in the state of Mato Grosso.