Temporal trend and spatial distribution of acute lymphoblastic leukemia in Iranian children during 2006 -2014: A Mixed Ecological Study

Abstract

The most common type of childhood cancers is acute lymphoblastic leukemia (ALL). The present study was conducted to determine the spatial-temporal epidemiological status of ALL in Iran. METHODS: Using an exploratory mixed design, this ecological study examined 3769 under-15 children with ALL who were reported in the National Cancer Registry of Iran during 2006 to 2014. Data were analyzed using the Mann-Whitney U, Getis-Ord General G (GOGG), Optimized hot spot analysis (OHSA), and the Pearson correlation coefficient (PCC) at α2 range and the significance level of 0.05. RESULTS: The average annual incidence rate of the disease was 2.25 and the cumulative incidence rate was 21.31 per 100,000 under-15 children. The mean and standard deviation (SD) of patients' age were 5.90 ±3.68 and the peak incidence was observed among 2-5-year olds. No significant difference in the mean age between boys and girls (P = 0.261). The incidence of ALL was seasonal and more common during spring and summer. The Getis-Ord General G index was 0.358 and significant (P-value <0.001). Hot spots were identified in south, central and eastern Iran and cold spots in north and west of Iran. PCC between CIR and latitude was negative (r=-0.5086 P=0.0035) but between CIR and longitude was positive (r= 0.3474 P =0.0555). CONCLUSIONS: Compared to developed countries, the incidence of ALL in Iranian children is lower but increasing. Can be argued that the incidence of ALL is due to the synergism interaction between environmental, infectious, geographical and genetic risk factors.

Spatio-temporal Analysis of COVID-19: A Global Study

“…This will show the output's best possible results to identify hot and cold spots. OHSA demonstrates results at 90%, 95%, and 99% confidence levels (24).…”

“…In order to indicate more precise clusters of COVID-19 in the world, an optimized hot spot analysis (OHSA) was employed. This method, according to the Getis-Ord Gi*, with the optimization of distance band for determining hot and cold spots (24). Using incremental spatial correlation, OHSA automatically selects the optimal bandwidth value at which spatial autocorrelation and clustering intensity are maximum and then uses it as an analytical scale for the Getis-Ord Gi * statistic (24).…”

“…This method, according to the Getis-Ord Gi*, with the optimization of distance band for determining hot and cold spots (24). Using incremental spatial correlation, OHSA automatically selects the optimal bandwidth value at which spatial autocorrelation and clustering intensity are maximum and then uses it as an analytical scale for the Getis-Ord Gi * statistic (24). This will show the output's best possible results to identify hot and cold spots.…”

Temporal Trend and Spatial Distribution of Drug Poisoning in Semnan Province: A Retrospective Longitudinal Study

“…The Kuldorff's purely spatial scan statistic test and the Gini Optimized Cluster Collection method were used to detect the high-risk and low-risk clusters and estimate the relative risk of drug poisoning in any county of Semnan Province. This new method separates clusters on a more local scale and optimizes the radius of the circular scanning window for cluster detection, thereby demonstrating the best results in cluster detection (13,16,17).…”

“…The closer the value of the statistic is to +1, the more it is clustered, and the closer it is to -1, the more it is dispersed, Furthermore, if its value is zero, the spatial distribution of the phenomenon is random. The null hypothesis indicated that the distribution of drug poisoning was randomly dispersed in Semnan Province (13,16). The Kuldorff's purely spatial scan statistic test and the Gini Optimized Cluster Collection method were used to detect the high-risk and low-risk clusters and estimate the relative risk of drug poisoning in any county of Semnan Province.…”