scholarly journals Modelling local patterns of child mortality risk: a Bayesian Spatio-temporal analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue-Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.

scholarly journals Modelling Local Patterns of Child Mortality Risk. A Bayesian Spatio-Temporal Analysis.

2020 ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue Mendoza ◽  
Juan C. Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Greater Mexico ◽  
Spatio Temporal ◽  
Child Mortality Rate

Abstract Background: Globally, child mortality rate is still high; however, this figure is susceptible to be reduced implementing proper spatially-targeted health public policies. Due to its alarming rate in comparison to North American standards, child mortality is a particular health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods: In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span. Results: The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions: The identification of high-risk municipalities and risk trends may provide a useful input for policy-makers seeking to reduce the incidence of child mortality. The results provide evidence that support the use of geographical targeting in policy interventions.

scholarly journals Modelling Local Patterns of Child Mortality Risk. A Bayesian Spatio-Temporal Analysis.

2019 ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue Mendoza ◽  
Juan Carlos Trujillo
Keyword(s):  
High Risk ◽  
Mexico City ◽  
Child Mortality ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
The North ◽  
Medium Risk ◽  
Greater Mexico ◽  
Spatio Temporal

Abstract Background : At the international scale the number of child deaths is still high; however, this figure is susceptible to be reduced implementing proper spatially-targeted health public policies. Due to its alarming rate in comparison to North American standards, child mortality is a particular health concern in Mexico. Despite this fact, there remains a dearth of studies that address the spatial-temporal identification of child mortality in Mexico. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities. Methods : In order to control for space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology allows to model the geographical variation of child mortality risk across municipalities within the studied time span. Results : The analysis shows that most of the high-risk municipalities are in the north and west areas of Greater Mexico City, although there coexist some in the east; some of them presenting an increasing child mortality risk trend. The outcomes highlight some municipalities currently presenting a medium risk, but that, given their trend, are likely to become high risk after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period. Conclusions : The identification of high-risk municipalities and risk trends may provide a useful input to policy-makers seeking to reduce the incidence of child mortality. The results provide evidence to support geographical targeting for policy interventions.

scholarly journals Modelling Local Patterns of Children Mortality. A Bayesian Spatio-Temporal Analysis.

2019 ◽  
Author(s):  
Alejandro Lome-Hurtado ◽  
Jacques Lartigue Mendoza ◽  
Juan Carlos Trujillo
Keyword(s):  
High Risk ◽  
Mortality Risk ◽  
Temporal Analysis ◽  
Health Concern ◽  
North West ◽  
The North ◽  
Policy Interventions ◽  
Medium Risk ◽  
Spatio Temporal ◽  
Over Time

Abstract Background: The number of death children at the international scale are still high, but with proper spatially-targeted health public policies this number could be reduced. In Mexico, children mortality is a particular health concern due to its alarming rate all throughout North America. The aims of this study are i) to model the change of children mortality risk at the municipality level, (ii) to identify municipalities with high, medium and low risk over time and (iii) to ascertain potential high-risk municipalities across time, using local trends of each municipality in Greater Mexico City. Methods: The study uses Bayesian spatio-temporal analysis to control for space-time patterns of data. This allow to model the geographical variation of the municipalities within the time span studied. Results: The analysis shows that most of the high-risk municipalities are in the north, west, and some in the east; some of such municipalities show an increasing children mortality risk over time. The outcomes highlight some municipalities which show a medium risk currently but are likely to become high risk along the study period. Finally, the odds of children mortality risk illustrate a decreasing tendency over the 7-year framework. Conclusions: Identification of high-risk municipalities may provide a useful input to policy-makers seeking out to reduce the incidence of children mortality, since it would provide evidence to support geographical targeting for policy interventions.

scholarly journals Arabian Sea Tropical Cyclones: A Spatio-Temporal Analysis in Support of Natural Hazard Risk Appraisal in Oman

2021 ◽  
Author(s):  
Suad Al-Manji ◽  
Gordon Mitchell ◽  
Amna Al Ruheili
Keyword(s):  
High Risk ◽  
Tropical Cyclones ◽  
Natural Hazard ◽  
Temporal Distribution ◽  
Storm Surges ◽  
Temporal Analysis ◽  
The North ◽  
Risk Areas ◽  
Spatio Temporal ◽  
Extreme Winds

Tropical cyclones [TCs] are a common natural hazard that have significantly impacted Oman. Over the period 1881–2019, 41 TC systems made landfall in Oman, each associated with extreme winds, storm surges and significant flash floods, often resulting in loss of life and substantial damage to infrastructure. TCs affect Omani coastal areas from Muscat in the north to Salalah in the south. However, developing a better understanding of the high-risk regions is needed, and is of particular interest in disaster risk reduction institutions in Oman. This study aims to find and map TC tracks and their spatio-temporal distribution to landfall in Oman to identify the high-risk areas. The analysis uses Kernel Density Estimation [KDE] and Linear Direction Mean [LDM] methods to better identify the spatio-temporal distribution of TC tracks and their landfall in Oman. The study reveals clear seasonal and monthly patterns. This knowledge will help to improve disaster planning for the high-risk areas.

Patterns of low birth weight in greater Mexico City: A Bayesian spatio-temporal analysis

2021 ◽  
Vol 134 ◽  
pp. 102521
Author(s):  
Alejandro Lome-Hurtado ◽  
Guangquan Li ◽  
Julia Touza-Montero ◽  
Piran C.L. White
Keyword(s):  
Birth Weight ◽  
Low Birth Weight ◽  
Mexico City ◽  
Temporal Analysis ◽  
Greater Mexico ◽  
Spatio Temporal

scholarly journals Spatio-temporal epidemiology of the tuberculosis incidence rate in Iran 2008 to 2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Behzad Kiani ◽  
Amene Raouf Rahmati ◽  
Robert Bergquist ◽  
Soheil Hashtarkhani ◽  
Neda Firouraghi ◽  
...  
Keyword(s):  
High Risk ◽  
Incidence Rate ◽  
Policy Development ◽  
Temporal Pattern ◽  
Temporal Analysis ◽  
High Rate ◽  
Spatial Scan Statistic ◽  
Cross Sectional ◽  
Risk Areas ◽  
Spatio Temporal

Abstract Background Effective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018. Methods This cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran’s I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05. Results The overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19–13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65–11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010–2014 and 2017–2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found. Conclusion The results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008–2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

scholarly journals Assessing the impact of feline immunodeficiency virus and bovine tuberculosis co-infection in African lions

2012 ◽  
Vol 279 (1745) ◽  
pp. 4206-4214 ◽  
Author(s):  
M. Maas ◽  
D. F. Keet ◽  
V. P. M. G. Rutten ◽  
J. A. P. Heesterbeek ◽  
M. Nielen
Keyword(s):  
Feline Immunodeficiency Virus ◽  
Bovine Tuberculosis ◽  
Temporal Analysis ◽  
Blood Chemistry ◽  
The North ◽  
Conservation Problem ◽  
Immunodeficiency Virus ◽  
Spatio Temporal ◽  
The Impact ◽  
African Lions

Bovine tuberculosis (BTB), caused by Mycobacterium bovis , is a disease that was introduced relatively recently into the Kruger National Park (KNP) lion population. Feline immunodeficiency virus (FIV ple ) is thought to have been endemic in lions for a much longer time. In humans, co-infection between Mycobacterium tuberculosis and human immunodeficiency virus increases disease burden. If BTB were to reach high levels of prevalence in lions, and if similar worsening effects would exist between FIV ple and BTB as for their human equivalents, this could pose a lion conservation problem. We collected data on lions in KNP from 1993 to 2008 for spatio-temporal analysis of both FIV ple and BTB, and to assess whether a similar relationship between the two diseases exists in lions. We found that BTB prevalence in the south was higher than in the north (72 versus 19% over the total study period) and increased over time in the northern part of the KNP (0–41%). No significant spatio-temporal differences were seen for FIV ple in the study period, in agreement with the presumed endemic state of the infection. Both infections affected haematology and blood chemistry values, FIV ple in a more pronounced way than BTB. The effect of co-infection on these values, however, was always less than additive. Though a large proportion (31%) of the lions was co-infected with FIV ple and M. bovis , there was no evidence for a synergistic relation as in their human counterparts. Whether this results from different immunopathogeneses remains to be determined.

scholarly journals African Swine Fever spread across Asia, 2018---2019

2020 ◽  
Author(s):  
Michael Ward ◽  
Ellen Mighell
Keyword(s):  
African Swine Fever Virus ◽  
African Swine Fever ◽  
Temporal Analysis ◽  
The Philippines ◽  
Control Measures ◽  
The South ◽  
Start Date ◽  
North East ◽  
The North ◽  
Spatio Temporal

African Swine Fever Virus (ASFV) is a highly contagious pathogen causing disease in pigs, commonly characterised by acute haemorrhagic fever. Prior to August 2018, African Swine Fever (ASF) had not been reported in Asia, but has since spread throughout China, Mongolia, Korea, Vietnam, Laos, Cambodia, Myanmar, the Philippines, Hong Kong, Indonesia, Timor-Leste and Papua New Guinea. Using data collated from reports of confirmed cases, we applied spatio-temporal analysis to describe ASFV spread throughout Asia, from 1 August 2018 (reported start date) to 31 December 2019. Analysis revealed a propagating epidemic of ASFV throughout Asia, with peaks corresponding to increased reports from China, Vietnam and Laos. Two clusters of reported outbreaks were found. During the epidemic, ASFV primarily spread from the North-East to the South-East: a larger, secondary cluster in the North-East represented earlier reports, whilst the smaller, primary cluster in the South-East was characterised by later reports. Significant differences in country-specific epidemics, morbidity, mortality and unit types were discovered, likely attributable to differences in prevention, surveillance and control measures. The initial number of outbreaks and enterprise size are likely predictors of the speed of spread and the effectiveness of ASFV stamping out procedures. Biosecurity methods, wild boar populations and the transportation of pigs and movement of infected fomites are discussed as likely risk factors for facilitating ASFV spread across Asia.

scholarly journals Public health monitoring using Geographic Information Systems: case viral hepatitis E

2021 ◽  
Vol 319 ◽  
pp. 01083
Author(s):  
El Omari Hajar ◽  
Abdelkader Chahlaoui ◽  
Ouarrak Khadija ◽  
Adel Kharroubi
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
High Risk ◽  
Viral Hepatitis ◽  
Temporal Analysis ◽  
Hepatitis E ◽  
Geographic Information ◽  
Average Risk ◽  
Health Events ◽  
Spatio Temporal

Among the major parasitic diseases having major health and socio-economic impacts in the world and in Morocco, are viral hepatitis. These are acute inflammations of the liver caused by a virus. The 3 most frequently encountered viruses are viruses A, B, C. The objective of this study is to map health events, in our case the incidence of viral hepatitis E in the different prefectures of the region of Meknes-Fez by creating a database containing geographic and health parameters in geographic information system (GIS). This database was then used to create the risk map which identifies the high-risk prefectures. This study shows that the average incidence of viral hepatitis H is higher in the prefecture of Meknes during all the years of the study, with a high risk compared to other prefectures and provinces which have an average risk. Indeed, the mapping of health events is a descriptive tool implemented to evaluate the spatial disparities of incidence, which allowed us to perform a spatio-temporal analysis of the epidemic. Spatial technologies, such as geographic information systems (GIS), offer a new option for disease prevention, predicting risk locations based on factors favoring the emergence or re-emergence of the epidemic.

scholarly journals Comprehensive Spatio-Temporal Analysis of Travel Climate Comfort Degree and Rainstorm-Flood Disaster Risk in the China–Russia Border Region

2020 ◽  
Vol 12 (8) ◽  
pp. 3254
Author(s):  
Yezhi Zhou ◽  
Juanle Wang ◽  
Elena Grigorieva ◽  
Eugene Egidarev ◽  
Wenxuan Zhang
Keyword(s):  
Temporal Analysis ◽  
Border Region ◽  
Risk Level ◽  
Risk Area ◽  
High Risk Area ◽  
The North ◽  
Time Space ◽  
Spatial Regularity ◽  
Spatio Temporal ◽  
Suitable Area

Infrastructure and tourism is gradually increasing along the China–Russia border with the development of the China–Mongolia–Russia economic corridor. Facing the issues of thermal comfort and rainstorm-flood risk in the neighborhood area between China and Russia, we constructed homologous evaluation models to analyze spatial regularity and internal variations of their effect. Among the results, approximately 55% of the area was classified into the categories of “comfort” and “high comfort” in summer. Oppositely, the situation of most areas in winter corresponds to physical discomfort. On the other hand, the high-risk area of rainstorm-flood in spring and summer is principally located in the northern and southern regions, respectively, while this is further expanded in autumn. After that, the risk level turns to medium and low. Subsequently, a comprehensive assessment coordinate system of the two results was constructed to identify the distribution pattern of a seasonal suitable area for traveling in binary ways. The evaluation shows that Great Khingan Range in the north-western Heilongjiang province is the preferable place among most of seasons, especially in summer. While on the Russian side, the corresponding area is mainly spread over its southern coastal cities. The study is expected to provide recommendations for reasonable year-round travel time, space selection, and risk decision support for millions of people traveling between China and Russia.

Sign in / Sign up

Export Citation Format

Share Document