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Time Series Analysis of Cutaneous Leishmaniasis in Sabzevar Northeastern Iran Using Segmented Regression Model

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Time Series Analysis of Cutaneous Leishmaniasis in Sabzevar Northeastern Iran Using Segmented Regression Model International Journal of Epidemiologic Research Archivedoi:10.34172/ijer.2020. of SID 18 2020 Summer;7(3):101-106 http://ijer.skums.ac.ir Original Article Time Series Analysis of Cutaneous Leishmaniasis in Sabzevar Northeastern Iran Using Segmented Regression Model Hadis Barati1 ID , Erfan Ayubi2 ID , Sohrab Iranpour3 ID , Mohammad Barati4 ID , Ahmad Allah-Abadi1 ID , Seyed Saeed Hashemi- Nazari5* ID 1Leishmaniasis Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran. 2Department of Community Medicine, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran. 3Social Determinants of Health Research Center, Ardabil University of Medical Sciences, Ardabil, Iran. 4Infectious Diseases Research Center, AJA University of Medical Sciences, Tehran, Iran. 5Department of Epidemiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran. *Corresponding Author: Abstract Seyed Saeed Hashemi- Background and aims: Cutaneous leishmaniasis (CL) is one of the most important parasitic diseases in Nazari, Department of Epidemiology, Shahid the world. Sabzevar city is endemic area for CL in the north east of Iran. The aim of this study was to Beheshti University of evaluate the time distribution of cutaneous leishmaniasis (CL) in Sabzevar County using the segmented Medical Sciences, Tehran, regression model. Iran. Tel: +989125779300 Methods: This ecological study used the existing data related to the rural districts of Sabzevar County Email: saeedh_1999@yahoo. that were obtained from the Health Deputy of this county during 2011-2017. In addition, the segmented com regression model was applied to evaluate the time trend of CLs. Finally, Joinpoint software was used for time series analysis. Results: A total of 1912 CL cases occurred in Sabzevar County from 2011 to 2017, with an incidence rate of 93.61 per 100 000. The highest and lowest observed incidence rates were in 2011 (25 per Received: 24 Feb. 2020 Accepted: 20 June 2020 10 000 persons) and 2015 (3.24 per 10 000 persons), respectively. Based on the results, the annual ePublished: 28 Sep. 2020 incidence of CL in the intended region decreased and the annual percent change was equal to -22.40. Further, the time series analysis using segmented regression by rural districts showed a change point in the trend of the incidence of leishmaniasis in three rural districts (Pain Joveyn and Joghatai in 2014 and Qasabeh-ye Sharqi in 2013). In other words, the trend was different before and after the change point in the mentioned districts. Conclusion: In general, the results indicated that interventional, preventive, and therapeutic measures for breaking the chain of CL transmission in Sabzevar have been desirable in recent years. Eventually, it is suggested that further time-series studies be conducted at the level of the month or a longer interval in order to better evaluate the period effect and secular trend. Keywords: Cutaneous leishmaniasis, Segmented regression model, Sabzevar Introduction places.6 Therefore, the investigation of the epidemiological Cutaneous leishmaniasis (CL), as a neglected disease, is aspects of CL can play an important role in its reduction. one of the most important parasitic diseases in the world.1 More precisely, monitoring the leishmaniasis and its There is no determined treatment for leishmaniasis, reservoirs in different regions, especially in indigenous and several issues are frequently reported in this regard, areas, is extremely necessary for preventing the occurrence including inappropriate treatment, failure to treat, and of the disease, its complications, and the high cost of disease relapse.2 Nearly 90% of cases occur in Afghanistan, treatment.7-10 Algeria, Iran, Iraq, Saudi Arabia, Syria, Brazil, and Peru.3 The determination of its incidence pattern over time Iran is regarded as one of the main foci of Leishmaniosis is one of the important determinants of surveillance, in the world. The annual frequency of leishmaniasis in Iran monitoring, and health planning. It is believed that is more than 20 000 cases,4 and its prevalence is increasing providing epidemiological data on the trend of incidence, due to environmental changes (caused by crises, travel, mortality, or the risk factors of the disease plays an and migration) and malnutrition.. The epidemiological important role in preventing adverse outcomes. In other pattern of CL has changed in recent years and has led to words, providing evidence and information about the an increase in the incidence of disease in non-endemic trend of a disease over time can have an essential role areas and the emergence of new foci of the disease in some in evaluating the health plans and development of the © 2020 The Author(s); Published by Shahrekord University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. www.SID.ir Barati et al Archive of SID indicators of a community.11,12 time, considering the assumption that the incidence of The segmented regression model is one of the appropriate years x to year x-1 is constant. methods for evaluating the incidence of a disease, which The following regression model was used to estimate of allows determining the number and location of changes in APC for a series of data. 13-15 the incidence of a given disease over a period of time. Log (RX) = b0 + b1X The estimation of the annual percentage changes (APC) Where log (Rx) is the natural logarithm of the rate in and the average of annual changes is possible by using year x. The APC estimation from year x to year x+1 is this regression model. These two indexes indicate the equal to trend of incidence. The segmented linear regression is a b++ bX( 1) b + bX( ) ee01 − 01 useful instrument for describing the trend of data changes, RRXX+1 − b += ×=×=−×1 Xe1 100 b+ bX( ) 100( 1) 100 01 particularly data on the incidence of disease or mortality. RX e Therefore, the present study applied the segmented regression model to evaluate the time distribution of CL In addition, AAPC is applied to provide a summary of in Sabzevar County so that the results can be used to the time trend and a single index for the time trend. This promote prevention and control programs in this county. index is a weighted average of the APC obtained from the regression model corresponding to each segment. Weights Materials and Methods are equal to the APC time interval. Study Site The following formula was used to estimate the AAPC. The present ecological study used the existing data related Ówb to the rural districts of Sabzevar county. The geographical AAPC= Expii −×1 100 Ó units of the study were 24 villages in this county. It should wi be noted that Sabzevar is located in the northeast of Iran with about 57° 67’ N latitude and 36° 20’ E longitude. The bis value represents the slope of the line (regression coefficient) for each section over a period of time and Data Collection wis is the length of each segment over a period of time. The data of people suffering from CL and treated in the Further, the confidence interval for AAPC and APC is health care centers of Sabsevar during 2011-2017 were based on the normal distribution and the t distribution, collected from the Health Deputy of this county. Data respectively. Joinpoint software was used for time series were collected on a monthly basis and classified according analysis. The random error variable in the segment to age, gender, and the rural district, and the incidence of regression model is homoscedastic if the variance of the the disease was calculated by year. errors is constant. Otherwise, the error is heteroscedastic. The assumption of homoscedasticity does not frequently Statistical Analysis exist, especially when the variance of the error varies greatly In this study, a segmented linear regression was used to over time. Considering the changes in the frequency of the identify the time pattern of leishmaniasis. It is a method leishmaniasis over time in the intended population and for the segmentation of the nonlinear regression model for having a more conservative state in the analyses, the into separate linear fragments. These fragments are random variable error was considered heteroscedastic. In separated by the change point. The optimal number and Joinpoint software, the inequality of variance was checked location of the change-point were estimated using the grid in several ways. Regarding the nature of the dependent search method. variable, which is the type of count, the variance of the For each geographic unit i, the mean of the regression random variable was determined using the Poisson variance function is equal to option, and the parameters of the segmented regression + + model were estimated as well. The P value of the test was E( yx| ) =ββ0 +i ,1 x + δ i ,1( x − τ i ,1 ) ++ δik, ( x − τ ik, ) estimated applying the permutation distribution of the ii test statistic and obtained through 4499 permutations. where ki and τ represent the number of unknown change- points and the change-points, respectively, and β and δ Results denote the parameters of regression. In this study, the In general, 1912 cases of CL (93.61 per 10 000) were natural logarithm of the annual incidence of CL and the observed in the whole region under study during 2011- intended years (2011-2017) were considered as dependent 2017. The largest number of CL cases (511) occurred and independent variables, respectively. in 2011 with an incidence rate of 25 per 10 000 persons whereas the least number was found in 2015 with an The Estimation of Annual Percent Changes and Average incidence rate of 3.30 per 10 000 persons in the entire Annual Percent Changes (AAPC) region under investigation.
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