Pulmonary tuberculosis space-time clustering and spatial variation in temporal trends in Portugal, 2000-2010: an updated analysis

Spatial distribution and determinants of tuberculosis incidence in Mozambique: A nationwide Bayesian disease mapping study

INTRODUCTION

Mozambique is a high-burden country for tuberculosis (TB). International studies show that TB is a disease that tends to cluster in specific regions, and different risk factors (HIV prevalence, migration, overcrowding, poverty, house condition, temperature, altitude, undernutrition, urbanization, and inadequate access to TB diagnosis and treatment) are reported in the literature to be associated with TB incidence. Although Mozambique has a higher burden of TB, the spatial distribution, and determinants of TB incidence at the sub-national level have not been studied yet for the whole country. Therefore, we aimed to analyze the spatial distribution and determinants of tuberculosis incidence across all 154 districts of Mozambique and identify the hotspot areas.

METHOD

We conducted an ecological study with the district as our unit of analysis, where we included all cases of tuberculosis diagnosed in Mozambique between 2016 and 2020. We obtained the data from the Mozambique Ministry of Health and other publicly available open sources. The predictor variables were selected based on the literature review and data availability at the district level in Mozambique. The parameters were estimated through Bayesian hierarchical Poisson regression models using Markov Chain Monte Carlo simulation.

RESULTS

A total of 512 877 people were diagnosed with tuberculosis in Mozambique during our five-year study period. We found high variability in the spatial distribution of tuberculosis incidence across the country. Sixty-two districts out of 154 were identified as hotspot areas. The districts with the highest incidence rate were concentrated in the south and the country's central regions. In contrast, those with lower incidence rates were mainly in the north. In the multivariate analysis, we found that TB incidence was positively associated with the prevalence of HIV (RR: 1.23; 95 % CrI 1.13 to 1.34) and negatively associated with the annual average temperature (RR: 0.83; 95 % CrI 0.74 to 0.94).

CONCLUSION

The incidence of tuberculosis is unevenly distributed across the country. Lower average temperature and high HIV prevalence seem to increase TB incidence. Targeting interventions in higher-risk areas and strengthening collaboration between HIV and TB programs is paramount to ending tuberculosis in Mozambique, as established by the WHO's End TB strategy and the Sustainable Development Goals.

Spatiotemporally Comparative Analysis of HIV, Pulmonary Tuberculosis, HIV-Pulmonary Tuberculosis Coinfection in Jiangsu Province, China

Purpose

Pulmonary tuberculosis (PTB) is a severe chronic communicable disease that causes a heavy disease burden in China. Human Immunodeficiency Virus (HIV) and PTB coinfection dramatically increases the risk of death. This study analyzes the spatiotemporal dynamics of HIV, PTB and HIV-PTB coinfection in Jiangsu Province, China, and explores the impact of socioeconomic determinants.

Patients and Methods

The data on all notified HIV, PTB and HIV-PTB coinfection cases were extracted from Jiangsu Provincial Center for Disease Control and Prevention. We applied the seasonal index to identify high-risk periods of the disease. Time trend, spatial autocorrelation and SaTScan were used to analyze temporal trends, hotspots and spatiotemporal clusters of diseases. The Bayesian space-time model was conducted to examine the socioeconomic determinants.

Results

The case notification rate (CNR) of PTB decreased from 2011 to 2019 in Jiangsu Province, but the CNR of HIV and HIV-PTB coinfection had an upward trend. The seasonal index of PTB was the highest in March, and its hotspots were mainly distributed in the central and northern parts, such as Xuzhou, Suqian, Lianyungang and Taizhou. HIV had the highest seasonal index in July and HIV-PTB coinfection had the highest seasonal index in June, with their hotspots mainly distributed in southern Jiangsu, involving Nanjing, Suzhou, Wuxi and Changzhou. The Bayesian space-time interaction model showed that socioeconomic factor and population density were negatively correlated with the CNR of PTB, and positively associated with the CNR of HIV and HIV-PTB coinfection.

Conclusion

The spatial heterogeneity and spatiotemporal clusters of PTB, HIV and HIV-PTB coinfection are exhibited obviously in Jiangsu. More comprehensive interventions should be applied to target TB in the northern part. While in southern Jiangsu, where the economic level is well-developed and the population density is high, we should strengthen the prevention and control of HIV and HIV-PTB coinfection.

Detection of areas vulnerable to scorpionism and its association with environmental factors in São Paulo, Brazil

Accidents caused by scorpions are considered a neglected condition and represent a major health problem in most tropical countries, especially for children and elderly people. In Brazil, scorpionism is recurrent in the southeast region, mainly in the state of São Paulo, due to the progressive increase in scorpions found in urban habitats. Thus, our study aimed to provide better insights into the geographic and epidemiological characteristics of scorpion envenomation in São Paulo state and identify the environmental factors that are associated with these accidents. This is an ecological and retrospective study with secondary data on scorpion accidents in the state of São Paulo from 2008 to 2018 obtained from the Notifiable Disease Information System. The SatScan software was used to identify the higher- and lower-risk spatiotemporal clusters. A total of 145,464 scorpion sting cases were recorded in the state of São Paulo, between 2008 and 2018; there was a four-fold increase in the incidence rate. Accidents occurred more frequently in the spring season, wherein higher-risk clusters were in the north and northwest regions of the state. High temperatures, low precipitation, and poor natural vegetation are associated with higher risk areas. Our study mapped vulnerable areas for scorpion accidents that can aid in the design of efficient public health policies, which should be intensified during the spring season.

Distribution of bacteriologically positive and bacteriologically negative pulmonary tuberculosis in Northwest China: spatiotemporal analysis

Pulmonary tuberculosis (PTB) is a major health issue in Northwest China. Most previous studies on the spatiotemporal patterns of PTB considered all PTB cases as a whole; they did not distinguish notified bacteriologically positive PTB (BP-PTB) and notified bacteriologically negative PTB (BN-PTB). Thus, the spatiotemporal characteristics of notified BP-PTB and BN-PTB are still unclear. A retrospective county-level spatial epidemiological study (2011-2018) was conducted in Shaanxi, Northwest China. In total, 44,894 BP-PTB cases were notified, with an average annual incidence rate of 14.80 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BP-PTB ranged from 0.19 to 0.49 (P < 0.001). Anselin's local Moran's I analysis showed that the high-high (HH) cluster for notified BP-PTB incidence was mainly located in the southernmost region. The primary spatiotemporal cluster for notified BP-PTB (LLR = 612.52, RR = 1.77, P < 0.001) occurred in the central region of the Guanzhong Plain in 2011. In total, 116,447 BN-PTB cases were notified, with an average annual incidence rate of 38.38 per 100,000 persons between 2011 and 2018. Global Moran's I values for notified BN-PTB ranged from 0.39 to 0.69 (P < 0.001). The HH clusters of notified BN-PTB were mainly located in the north between 2011 and 2014 and in the south after 2015. The primary spatiotemporal cluster for notified BN-PTB (LLR = 1084.59, RR = 1.85, P < 0.001) occurred in the mountainous areas of the southernmost region from 2014 to 2017. Spatiotemporal clustering of BP-PTB and BN-PTB was detected in the poverty-stricken mountainous areas of Shaanxi, Northwest China. Our study provides evidence for intensifying PTB control activities in these geographical clusters.

Intra-urban variation in tuberculosis and community socioeconomic deprivation in Lisbon metropolitan area: a Bayesian approach

Background

Multidrug resistant tuberculosis (MDR-TB) is a recognized threat to global efforts to TB control and remains a priority of the National Tuberculosis Programs. Additionally, social determinants and socioeconomic deprivation have since long been associated with worse health and perceived as important risk factors for TB. This study aimed to analyze the spatial distribution of non-MDR-TB and MDR-TB across parishes of the Lisbon metropolitan area of Portugal and to estimate the association between non-MDR-TB and MDR-TB and socioeconomic deprivation.

Methods

In this study, we used hierarchical Bayesian spatial models to analyze the spatial distribution of notification of non-MDR-TB and MDR-TB cases for the period from 2000 to 2016 across 127 parishes of the seven municipalities of the Lisbon metropolitan area (Almada, Amadora, Lisboa, Loures, Odivelas, Oeiras, Sintra), using the Portuguese TB Surveillance System (SVIG-TB). In order to characterise the populations, we used the European Deprivation Index for Portugal (EDI-PT) as an indicator of poverty and estimated the association between non-MDR-TB and MDR-TB and socioeconomic deprivation.

Results

The notification rates per 10,000 population of non-MDR TB ranged from 18.95 to 217.49 notifications and that of MDR TB ranged from 0.83 to 3.70. We identified 54 high-risk areas for non-MDR-TB and 13 high-risk areas for MDR-TB. Parishes in the third [relative risk (RR) = 1.281, 95% credible interval (CrI): 1.021–1.606], fourth (RR = 1.786, 95% CrI: 1.420–2.241) and fifth (RR = 1.935, 95% CrI: 1.536–2.438) quintile of socioeconomic deprivation presented higher non-MDR-TB notifications rates. Parishes in the fourth (RR = 2.246, 95% CrI: 1.374–3.684) and fifth (RR = 1.828, 95% CrI: 1.049–3.155) quintile of socioeconomic deprivation also presented higher MDR-TB notifications rates.

Conclusions

We demonstrated significant heterogeneity in the spatial distribution of both non-MDR-TB and MDR-TB at the parish level and we found that socioeconomically disadvantaged parishes are disproportionally affected by both non-MDR-TB and MDR-TB. Our findings suggest that the emergence of MDR-TB and transmission are specific from each location and often different from the non-MDR-TB settings. We identified priority areas for intervention for a more efficient plan of control and prevention of non-MDR-TB and MDR-TB.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s40249-022-00949-1.

Tuberculosis and Migrant Pathways in an Urban Setting: A Mixed-Method Case Study on a Treatment Centre in the Lisbon Metropolitan Area, Portugal

Tuberculosis (TB) is an infectious disease associated with poverty. In the European Union TB tends to concentrate in urban settings. In Lisbon, previous studies revealed, the presence of migrant populations from a high endemic country, is one of the risk factors contributing to TB. To better understand TB in foreign-born individuals in the Lisbon Metropolitan Area, a mixed-method case study was undertaken on a TB treatment centre in a high-risk part of urban Portugal. Quantitatively, annual TB cases were analysed from 2008 to 2018, dividing foreign-origin cases into recent migrants and long-term migrants. Qualitatively, we explored recent migrants’ reasons, experiences and perceptions associated with the disease. Our results showed that foreign-born individuals accounted for 45.7% of cases, mainly originated from Angola, Guinea-Bissau, and Cabo Verde. TB in recent migrants increased over the years for Angola and Guinea-Bissau, while for Cabo Verde TB cases were due to migrants residing in Portugal for more than 2 years. Recent migrants’ reasons to travel to Portugal were to study, to live and work, tourism, and seeking better healthcare. Visiting family and friends, historical links and common language were key drivers for the choice of country. Recent migrants and long-term migrants may present distinct background profiles associated with diagnosed TB.

Space-time clustering and temporal trends of hospitalizations due to pulmonary tuberculosis: potential strategy for assessing health care policies

BACKGROUND

Tuberculosis (TB) causes pressure on healthcare resources, especially in terms of hospital admissions, despite being considered an ambulatory care-sensitive condition for which timely and effective care in ambulatory setting could prevent the need for hospitalization. Our objectives were to describe the spatial and temporal variation in pulmonary tuberculosis (PTB) hospitalizations, identify critical geographic areas at municipality level and characterize clusters of PTB hospitalizations to help the development of tailored disease management strategies that could improve TB control.

METHODS

Ecologic study using sociodemographic, geographical and clinical information of PTB hospitalization cases from continental Portuguese public hospitals, between 2002 and 2016. Descriptive statistics, spatiotemporal cluster analysis and temporal trends were conducted.

RESULTS

The space-time analysis identified five clusters of higher rates of PTB hospitalizations (2002-16), including the two major cities in the country (Lisboa and Porto). Globally, we observed a -7.2% mean annual percentage change in rate with only one of the identified clusters (out of six) with a positive trend (+4.34%). In the more recent period (2011-16) was obtained a mean annual percentage change in rate of -8.12% with only one cluster identified with an increase trend (+9.53%).

CONCLUSIONS

Our results show that space-time clustering and temporal trends analysis can be an invaluable resource to monitor the dynamic of the disease and contribute to the design of more effective, focused interventions. Interventions such as enhancing the detection of active and latent infection, improving monitoring and evaluation of treatment outcomes or adjusting the network of healthcare providers should be tailored to the specific needs of the critical areas identified.

Descriptive Spatial Analysis of Human-Elephant Conflict (HEC) Distribution and Mapping HEC Hotspots in Keonjhar Forest Division, India

Escalation of human-elephant conflict (HEC) in India threatens its Asian elephant (Elephas maximus) population and victimizes local communities. India supports 60% of the total Asian elephant population in the world. Understanding HEC spatial patterns will ensure targeted mitigation efforts and efficient resource allocation to high-risk regions. This study deals with the spatial aspects of HEC in Keonjhar forest division, where 345 people were killed and 5,145 hectares of croplands were destroyed by elephant attacks during 2001–2018. We classified the data into three temporal phases (HEC1: 2001–2006, HEC2: 2007–2012, and HEC3: 2013–2018), in order to (1) derive spatial patterns of HEC; (2) identify the hotspots of HEC and its different types along with the number of people living in the high-risk zones; and (3) assess the temporal change in the spatial risk of HEC. Significantly dense clusters of HEC were identified in Keonjhar and Ghatgaon forest ranges throughout the 18 years, whereas Champua forest range became a prominent hotspot since HEC2. The number of people under HEC risk escalated from 14,724 during HEC1 and 34,288 in HEC2, to 65,444 people during HEC3. Crop damage was the most frequent form of HEC in the study area followed by house damage and loss of human lives. Risk mapping of HEC types and high priority regions that are vulnerable to HEC, provides a contextual background for researchers, policy makers and managers.

Using Bayesian spatial models to map and to identify geographical hotspots of multidrug-resistant tuberculosis in Portugal between 2000 and 2016

Multidrug-resistant tuberculosis (MDR-TB) is a major threat to the eradication of tuberculosis. TB control strategies need to be adapted to the necessities of different countries and adjusted in high-risk areas. In this study, we analysed the spatial distribution of the MDR- and non-MDR-TB cases across municipalities in Continental Portugal between 2000 and 2016. We used Bayesian spatial models to estimate age-standardized notification rates and standardized notification ratios in each area, and to delimitate high- and low-risk areas, those whose standardized notification ratio is significantly above or below the country’s average, respectively. The spatial distribution of MDR- and non-MDR-TB was not homogeneous across the country. Age-standardized notification rates of MDR-TB ranged from 0.08 to 1.20 and of non-MDR-TB ranged from 7.73 to 83.03 notifications per 100,000 population across the municipalities. We identified 36 high-risk areas for non-MDR-TB and 8 high-risk areas for MDR-TB, which were simultaneously high-risk areas for non-MDR-TB. We found a moderate correlation (ρ = 0.653; 95% CI 0.457–0.728) between MDR- and non-MDR-TB standardized notification ratios. We found heterogeneity in the spatial distribution of MDR-TB across municipalities and we identified priority areas for intervention against TB. We recommend including geographical criteria in the application of molecular drug resistance to provide early MDR-TB diagnosis, in high-risk areas.

Spatial-temporal analysis of tuberculosis in Chongqing, China 2011-2018

BACKGROUND

China is a country with a high burden of pulmonary tuberculosis (PTB). Chongqing is in the southwest of China, where the notification rate of PTB ranks tenth in China. This study analyzed the temporal and spatial distribution characteristics of PTB in Chongqing in order to improve TB control measures.

METHODS

A spatial-temporal analysis has been performed based on the data of PTB from 2011 to 2018, which was extracted from the National Surveillance System. The effect of TB control was measured by variation trend of pathogenic positive PTB notification rate and total TB notification rate. Time series, spatial autonomic correlation and spatial-temporal scanning methods were used to identify the temporal trends and spatial patterns at county level.

RESULTS

A total of 188,528 cases were included in this study. A downward trend was observed in PTB between 2011 and 2018 in Chongqing. The peak of PTB notification occurred in late winter and early spring annually. By calculating the value of Global Moran's I and Local Getis's Gi*, we found that PTB was spatially clustered and some significant hot spots were detected in the southeast and northeast of Chongqing. One most likely cluster and three secondary clusters were identified by Kulldorff's scan spatial-temporal Statistic.

CONCLUSIONS

This study identified seasonal patterns and spatial-temporal clusters of PTB cases in Chongqing. Priorities should be given to southeast and northeast of Chongqing for better TB control.

The ongoing challenge of Pulmonary Tuberculosis in Southern Tunisia: A review of a 22-year period

BACKGROUND

Despite the wide use of anti-tuberculosis drugs, pulmonary tuberculosis (PTB) remains one of the most important causes of mortality and morbidity, particularly in developing countries. Therefore, combining clinical and epidemiological approach would be of a great benefit. Our study aimed to describe the epidemiological and clinical specificities of PTB and its recent chronological trends.

METHODS

We conducted a retrospective study of all PTB new cases of any age diagnosed between 1995 and 2016 in Southern Tunisia. We applied the direct method of age-standardization using the World Standard Population to compute the age standardized incidence rate (ASIR) and the age standardized mortality rate (ASMR) per 100 000 inhabitants.

RESULTS

We recorded 1121 new cases with PTB among 2771 new cases of tuberculosis (40.5%). The ASIR of PTB was 5.3/100 000 inhabitants/year and didn't change over the study period (rho=0.3; P=0.2). Patients with PTB were mainly aged between 15 and 59 years (n=861; 76.8%) and came from urban areas (n=600; 55%). The median duration of treatment was 7.6 months (IQR=[6-8 months]). Successful outcome was notified in 1075 cases (95.9%). Forty-one patients died yielding an ASMR of 0.18/100 000 inhabitants/year. Factors statistically associated with unsuccessful outcome included age≥60 years (OR=5; P<0.001) and shorter treatment duration (6.15 months vs 7.76 months; P<0.001).

CONCLUSION

In contrast to the decline in the global PTB incidence reported worldwide and in the neighboring countries, our study revealed no significant change in the PTB rates from 1995 to 2016. Therefore, tools and strategies used to manage PTB should be strengthened by a substantial effort in both basic science and epidemiology to have better incidence curves.

Analysis on spatial-temporal distribution characteristics of smear positive pulmonary tuberculosis in China, 2004-2015

BACKGROUND

In China, tuberculosis (TB) is still a major infectious disease threatening people's health. Smear positive pulmonary TB is one of the most common infectious forms of TB and it might easily cause the outbreak in some areas. With a better understanding of the spatial-temporal variations of smear positive PTB, we would reach the targets for TB prevention and controlling, identify high-risk areas and periods. Thus, the aim of this study was to investigate the spatial-temporal variations of smear positive PTB.

METHODS

Provincial level data of reported smear positive PTB monthly cases and incidence from January 2004 to December 2015 were obtained from the National Scientific Data Sharing Platform for Population and Health of China. Purely spatial-temporal descriptive analysis was used to characterize the distribution patterns of smear positive PTB. The global spatial auto-correlation statistics (Moran's I) and the local indicators of spatial association (LISA) were conducted to identify the spatial auto-correlation and high risk areas of smear positive PTB cases. Furthermore, the space-time scan statistic was adopted to detect the spatial-temporal clusters in different periods.

RESULTS

A total of 4,711,571 smear positive PTB cases were notified in China with an average annual incidence of 29.59/100,000. The proportion of male in different age groups were obviously higher than that of women. The largest number of cases was reported in the 20-24 years age group. Time-series analysis indicated that monthly incidence appeared a clearly seasonality and periodicity, which the seasonal peaks occurred in January and March. Smear positive PTB cases had a positive global spatial auto-correlation in 2013-2015 (Moran's I=0.186, P=0.046). Spatial clusters were identified in four periods, located in the different regions. The time period of 2004-2006, the most likely spatial-temporal cluster (RR=1.69, P<0.001) was mainly located in Hubei, Hunan, Jiangxi and Anhui of central China, clustering in the time frame from January 2005 to June 2006. During 2007-2009, the most likely spatial-temporal cluster (RR=5.65, P<0.001) was located in Guizhou, clustering in the time frame from January to December 2009. The spatial-temporal clustering in the years 2010-2012 showed the most likely cluster (RR=1.44, P<0.001) was distributed in Anhui, Hunan, Hubei, Jiangxi and Guangdong with the time frame from January 2010 to June 2011. During 2013-2015, the most likely cluster (RR=1.86, P<0.001) was detected in Hunan, Hubei, Jiangxi and Guangdong from February 2013 to June 2014.

CONCLUSIONS

This study identified the spatial-temporal patterns of smear positive PTB in China and demonstrated the capability and utility of the spatial-temporal approach in epidemiology. The results of this study would contribute to estimating the high risk periods and areas, and to providing more useful information for policy-making.

Unsuccessful treatment in pulmonary tuberculosis: factors and a consequent predictive model

Background

Cure is particularly valuable in pulmonary cases (PTB), as unsuccessful treatment fuels incidence and resistance to antibiotics. This study aims to identify individual factors of PTB unsuccessful treatment in Portugal and to develop a consequent predictive model.

Methods

Using the Portuguese TB surveillance database (SVIG-TB), PTB cases older than 15 years notified from 2000 to 2012 in Continental Portugal were analyzed. Unsuccessful treatment included the WHO categories (failure, default, death and transferred out). Based on a literature review, predictors involved sociodemographic, behavioral, disease-related and treatment-related factors. Binary logistic regression was used to estimate unsuccessful treatment factors and to develop the predictive risk model.

Results

The unsuccessful outcome rate in PTB patients was of 11.9%. The predictive model included the following factors: TB/HIV co-infection (OR 4.93), age over 64 years (OR 4.37), IV drugs abuse (OR 2.29), other diseases (excluding HIV and Diabetes, OR 2.09) and retreatment (OR 1.44), displaying a rather good validity.

Conclusion

The overall treatment unsuccessful treatment rate in PTB patients complies with the 85% WHO success threshold. The predictive model of unsuccessful treatment proved well. Nomogram representation allows an early, intuitive identification of PTB patients at increased risk. The model is liable to widespread use as a prognostic tool.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

Using the Kulldorff's scan statistical analysis to detect spatio-temporal clusters of tuberculosis in Qinghai Province, China, 2009-2016

BACKGROUND

Although the incidence of tuberculosis (TB) in most parts of China are well under control now, in less developed areas such as Qinghai, TB still remains a major public health problem. This study aims to reveal the spatio-temporal patterns of TB in the Qinghai province, which could be helpful in the planning and implementing key preventative measures.

METHODS

We extracted data of reported TB cases in the Qinghai province from the China Information System for Disease Control and Prevention (CISDCP) during January 2009 to December 2016. The Kulldorff's retrospective space-time scan statistics, calculated by using the discrete Poisson probability model, was used to identify the temporal, spatial, and spatio-temporal clusters of TB at the county level in Qinghai.

RESULTS

A total of 48,274 TB cases were reported from 2009 to 2016 in Qinghai. Results of the Kulldorff's scan revealed that the TB cases in Qinghai were significantly clustered in spatial, temporal, and spatio-temporal distribution. The most likely spatio-temporal cluster (LLR = 2547.64, RR = 4.21, P < 0.001) was mainly concentrated in the southwest of Qinghai, covering seven counties and clustered in the time frame from September 2014 to December 2016.

CONCLUSION

This study identified eight significant space-time clusters of TB in Qinghai from 2009 to 2016, which could be helpful in prioritizing resource assignment in high-risk areas for TB control and elimination in the future.

A decade of adverse drug events in Portuguese hospitals: space-time clustering and spatial variation in temporal trends

Background

The aim of this study is to identify the distribution by municipalities of adverse drug events (ADE) in Portugal, including adverse drug reactions (ADR) and accidental poisoning by drugs (AP), on municipality/years ADE rate clustering. Also we identify areas with different trends in time.

Methods

We used a national dataset of public hospital discharges in Continental Portugal from 2004 to 2013. Events were identified based on codes: from E930 to E949.9 (ADR) and from E850 to E858.9 (AP). Space-time clustering and spatial variation in temporal trends methods were applied in three different time-periods: globally, by year and grouped in 2 classes (periods of 5 years).

Results

A total of 9,320,076 patients were discharged within this period, with 133,688 patients (1.46%) having at least one ADE, 4% of them related with AP. Critical space-time identified clusters (p < 0.001) were the municipalities from Lisbon metropolitan area and Centro region area. The global rate increased at a 7.8% mean annual percentage change, with high space-time heterogeneity and variation in time trends clusters (p < 0.001). For whole period, 2004–2013, all clusters presented increasing trends. However when analyzed by period of 5 years we identified two clusters with decreasing trends in time in 2004–2008.

Conclusion

The impact of ADE is huge, with widely variations within country and in time, and represents an increasing challenge. Future research using individual and contextual risk factors are urgently needed to understand this spatiotemporal variability in order to promote local tailored and updated actions of prevention.

Identification of spatial and cohort clustering of tuberculosis using surveillance data from British Columbia, Canada, 1990-2013

Since 2000, the global incidence of tuberculosis (TB) has decreased by 1.5% per year, becoming increasingly clustered in key subpopulations in low incidence settings. TB clustering can manifest spatially from recent transmission, or in non-spatial cohort clusters resulting from reactivation of latent infection in populations with shared risk factors. Identifying and interrupting disease clusters is required to eliminate TB in low incidence countries. Here we demonstrate an analytical approach for detecting both spatial and cohort clustering of TB among population subgroups, and describe the value in differentiating these forms of clustering. TB cases in British Columbia meeting the Canadian case definition were geocoded and mapped using Geographic Information Systems (GIS). Incidence rates were calculated for three periods (1990-1997, n = 2556; 1998-2005, n = 2488; 2006-2013, n = 2225) among Canadian born (CB) and foreign-born (FB) populations using denominator data from the Canadian Census. Spatial clusters were identified using a scanning window statistic (SaTScan) and overlaid on provincial incidence maps. Country of birth (cohort) clustering in the FB was identified using Lorenz curves and Gini coefficients. TB incidence in the CB population was generally low, but punctuated with few areas of high incidence; the spatial clusters identified in the CB match previously identified clusters. TB incidence in the FB did not show spatially localized clusters. However, Lorenz curves revealed substantial, and increasing, cohort clustering in the FB in semi-urban and rural regions of British Columbia, and less pronounced, and decreasing, clustering in urban regions. In general, the TB incidence in groups defined by country of birth shifted over time to become increasingly uniform across regions. Our approach, based on spatial analysis and the application of Lorenz curves revealed a complex coexistence of spatial and cohort clustering. Spatial and cohort clusters require differing public health responses, and differentiating types of clustering can inform TB prevention programs.

Vaccination of Adult Patients with Systemic Lupus Erythematosus in Portugal

In the wake of the Portuguese vaccination program 50th anniversary it seems appropriate to review vaccination in patients with systemic lupus erythematosus. Controversial issues as regards the association between autoimmune diseases, infections, and vaccines are discussed as well as vaccine safety and efficacy issues as regards chronic immunosuppressant (IS) drug therapy. After a brief overview of national policies, specific recommendations are made as regards vaccination for adult patients with SLE with a particular focus on current IS therapy and unmet needs.

Spatio-Temporal Distribution Characteristics and Trajectory Similarity Analysis of Tuberculosis in Beijing, China

Tuberculosis (TB) is an infectious disease with one of the highest reported incidences in China. The detection of the spatio-temporal distribution characteristics of TB is indicative of its prevention and control conditions. Trajectory similarity analysis detects variations and loopholes in prevention and provides urban public health officials and related decision makers more information for the allocation of public health resources and the formulation of prioritized health-related policies. This study analysed the spatio-temporal distribution characteristics of TB from 2009 to 2014 by utilizing spatial statistics, spatial autocorrelation analysis, and space-time scan statistics. Spatial statistics measured the TB incidence rate (TB patients per 100,000 residents) at the district level to determine its spatio-temporal distribution and to identify characteristics of change. Spatial autocorrelation analysis was used to detect global and local spatial autocorrelations across the study area. Purely spatial, purely temporal and space-time scan statistics were used to identify purely spatial, purely temporal and spatio-temporal clusters of TB at the district level. The other objective of this study was to compare the trajectory similarities between the incidence rates of TB and new smear-positive (NSP) TB patients in the resident population (NSPRP)/new smear-positive TB patients in the TB patient population (NSPTBP)/retreated smear-positive (RSP) TB patients in the resident population (RSPRP)/retreated smear-positive TB patients in the TB patient population (RSPTBP) to detect variations and loopholes in TB prevention and control among the districts in Beijing. The incidence rates in Beijing exhibited a gradual decrease from 2009 to 2014. Although global spatial autocorrelation was not detected overall across all of the districts of Beijing, individual districts did show evidence of local spatial autocorrelation: Chaoyang and Daxing were Low-Low districts over the six-year period. The purely spatial scan statistics analysis showed significant spatial clusters of high and low incidence rates; the purely temporal scan statistics showed the temporal cluster with a three-year period from 2009 to 2011 characterized by a high incidence rate; and the space-time scan statistics analysis showed significant spatio-temporal clusters. The distribution of the mean centres (MCs) showed that the general distributions of the NSPRP MCs and NSPTBP MCs were to the east of the incidence rate MCs. Conversely, the general distributions of the RSPRP MCs and the RSPTBP MCs were to the south of the incidence rate MCs. Based on the combined analysis of MC distribution characteristics and trajectory similarities, the NSP trajectory was most similar to the incidence rate trajectory. Thus, more attention should be focused on the discovery of NSP patients in the western part of Beijing, whereas the northern part of Beijing needs intensive treatment for RSP patients.