Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru

Carrasco-Escobar, Gabriel; Schwalb, Alvaro; Tello-Lizarraga, Kelly; Vega-Guerovich, Percy; Ugarte-Gil, César

doi:10.1186/s40249-020-00647-w

Cited by 27 publications

(17 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of this study showed a spatial dependence in the occurrence of TB cases, with higher density in the Southern region of this municipality, over the years studied. It is important to consider that the tendency of TB is associated with multiple historical and social processes that involve social determinants of the health-disease process and demand individual, collective, and programmatic strategies of the social actors to eliminate it, especially in vulnerable populations ( 18 - 19 ) .…”

Section: Discussionmentioning

confidence: 99%

Tuberculosis associated with the living conditions in an endemic municipality in the North of Brazil*

André

Nogueira

Rodrigues

et al. 2020

Rev. Latino-Am. Enfermagem

View full text Add to dashboard Cite

Objective: to analyze the association between the occurrence of new tuberculosis cases and the Adapted Living Condition Index, and to describe the spatial distribution in an endemic municipality. Method: this is an analytical and ecological study that was developed from new cases in residents of an endemic municipality in the North Region of Brazil. The data were obtained from the Notifiable Diseases Information System and from the 2010 Demographic Census. The Adapted Living Conditions Index was obtained by factor analysis and its association with the occurrence of the disease was analyzed by means of the chi-square test. The type I error was set at 0.05. Kernel estimation was used to describe the density of tuberculosis in each census sector. Results: the incidence coefficient was 97.5/100,000 inhabitants. The data showed a statistically significant association between the number of cases and socioeconomic class, with the fact that belonging to the highest economic class reduces the chance of the disease occurring. The thematic maps showed that tuberculosis was distributed in a heterogeneous way with a concentration in the Southern region of the municipality. Conclusion: tuberculosis, associated with precarious living conditions, reinforces the importance of discussion on social determinants in the health-disease process to subsidize equitable health actions in risk areas, upon a context of vulnerability.

show abstract

Section: Discussionmentioning

confidence: 99%

Tuberculosis associated with the living conditions in an endemic municipality in the North of Brazil*

André

Nogueira

Rodrigues

et al. 2020

Rev. Latino-Am. Enfermagem

View full text Add to dashboard Cite

show abstract

“…Our study showed that the incidence of respiratory infectious diseases in Shandong Province is mainly in West Shandong and Central Shandong, followed by South Shandong. The incidence of respiratory infectious diseases in coastal areas is relatively well controlled, indicating that the distribution characteristics of respiratory infectious diseases are closely related to geographical and environmental factors [31,32]. The analysis of this study showed that there is obvious spatial clustering of each respiratory infectious disease.…”

Section: Discussionmentioning

confidence: 69%

Analysis of Spatial-Temporal Distribution of Respiratory Infectious Diseases in Shandong Province, China During 2005-2014

Li¹,

Chen²,

Zhang

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Little comprehensive information on overall epidemic trend of respiratory infectious diseases is available in Shandong Province, China. This study aimed to determine the spatiotemporal distribution and epidemic characteristics of respiratory infectious diseases.Methods: Time series was firstly performed to describe the temporal distribution feature of respiratory infectious diseases during 2005-2014 in Shandong Province. GIS Natural Breaks (Jenks) was applied to divide the average annual incidence of respiratory infectious diseases into five grades. Spatial empirical Bayesian smoothed risk maps and excess risk maps were further used to investigate spatial patterns of respiratory infectious diseases. Global and local Moran’s I statistics were used to measure the spatial autocorrelation. Spatial-temporal scanning was used to detect spatiotemporal clusters and identify high-risk locations. Results: A total of 537,506 cases of respiratory infectious diseases were reported in Shandong province during 2005-2014. The morbidity of respiratory infectious diseases had obvious seasonality with high morbidity in winter and spring. Local Moran’s I analysis showed that there were 5, 23, 24, 4, 20, 8, 14, 10 and 7 high-risk counties determined for influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella, respectively. The spatial-temporal clustering analysis determined that the most likely cluster of influenza A (H1N1), measles, tuberculosis, meningococcal meningitis, pertussis, scarlet fever, influenza, mumps and rubella included 74, 66, 58, 56, 22, 64, 2, 75 and 56 counties, and the time frame was November 2009, March 2008, January 2007, February 2005, July 2007, December 2011, November 2009, June 2012 and May 2005, respectively.Conclusions: There were obvious spatiotemporal clusters of respiratory infectious diseases in Shandong during 2005–2014. More attention should be paid to the epidemiological and spatiotemporal characteristics of respiratory infectious diseases to establish new strategies for its control.

show abstract

“…Finally, we relied on ward-level case notification data to ascertain TB transmission risk within wards. Although we accounted for some of this discrepancy in patient reporting patterns, some of the heterogeneity in case notifications could also reflect differences in access to TB care 28,29 (e.g., lower case notification due to lower case notification ratios), demographics 30 (e.g., clustering of migrants from other high incidence areas) or socio-economic differences 31 (e.g., poverty). The relative impact of geographic targeting in such instances may not be as substantial or as sustained.…”

Section: Discussionmentioning

confidence: 99%

Quantifying geographic heterogeneity in TB incidence and the potential impact of geographically targeted interventions in South and North City Corporations of Dhaka, Bangladesh: a model-based study

Shrestha

Reja²,

Gomes

et al. 2021

Epidemiol. Infect.

View full text Add to dashboard Cite

In rapidly growing, high burden urban centers, identifying tuberculosis (TB) transmission hotspots and understanding potential impact of interventions can inform future control and prevention strategies.Using data on local demography, TB reports, and patient reporting patterns in Dhaka South City Corporation (DSCC) and Dhaka North City Corporation (DNCC), Bangladesh, between 2010 and 2017, we developed maps of TB reporting rates across wards in DSCC and DNCC and identified wards with high rates of reported TB (i.e. "hotspots") in DSCC and DNCC. We developed ward-level transmission models and estimated the potential epidemiological impact of three TB interventions: active case finding (ACF), mass preventive therapy (PT), and a combination of ACF and PT, implemented either citywide or targeted to high-incidence hotspots. There was substantial geographic heterogeneity in the estimated TB incidence in both DSCC and DNCC: incidence in the highest-incidence wards was over ten times higher than in the lowest-incidence wards in each city corporation. ACF, PT and combined ACF plus PT delivered to 10% of the population reduced TB incidence by a projected 7-9%, 13-15%, and 19-23% over five years, respectively. Targeting TB hotspots increased the projected reduction in TB incidence achieved by each intervention 1.4-to 1.8-fold. The geographical pattern of TB notifications suggests high levels of ongoing TB transmission in DSCC and DNCC, with substantial heterogeneity at the ward level. Interventions that reduce transmission are likely to be highly effective and incorporating notification data at the local level can further improve intervention efficiency.

show abstract

Spatio-temporal co-occurrence of hotspots of tuberculosis, poverty and air pollution in Lima, Peru

Cited by 27 publications

References 29 publications

Tuberculosis associated with the living conditions in an endemic municipality in the North of Brazil*

Tuberculosis associated with the living conditions in an endemic municipality in the North of Brazil*

Analysis of Spatial-Temporal Distribution of Respiratory Infectious Diseases in Shandong Province, China During 2005-2014

Quantifying geographic heterogeneity in TB incidence and the potential impact of geographically targeted interventions in South and North City Corporations of Dhaka, Bangladesh: a model-based study

Contact Info

Product

Resources

About