Hotspot detection using space-time scan statistics on children under five years of age in Depok

Transcription

1 Hotspot detection using space-time scan statistics on children under five years of age in Depok Miranti Verdiana, and Yekti Widyaningsih Citation: AIP Conference Proceedings 1827, (2017); View online: View Table of Contents: Published by the American Institute of Physics Articles you may be interested in Application of hotspot detection using spatial scan statistic: Study of criminality in Indonesia AIP Conference Proceedings 1827, (2017); / Spatial modeling on the upperstream of the Citarum watershed: An application of geoinformatics AIP Conference Proceedings 1827, (2017); / Spatial panel data models of aquaculture production in West Sumatra province with random-effects AIP Conference Proceedings 1827, (2017); / Modeling the human development inde and the percentage of poor people using quantile smoothing splines AIP Conference Proceedings 1827, (2017); / A measure for objects clustering in principal component analysis biplot: A case study in inter-city buses maintenance cost data AIP Conference Proceedings 1827, (2017); / Multilevel modeling and panel data analysis in educational research (Case study: National eamination data senior high school in West Java) AIP Conference Proceedings 1827, (2017); /

2 Hotspot Detection using Space-time Scan Statistics on Children under Five Years of Age in Depok Miranti Verdiana a) and Yekti Widyaningsih b) Dept. Matematika FMIPA UI, Kampus Baru UI, Depok, 16424, Jawa Barat, Corresponding Author a) b) Abstract. Some problems that affect the health level in Depok are the high malnutrition rates from year to year and the more spread infectious and non-communicable diseases in some areas. Children under five years old is a vulnerable part of population to get the malnutrition and diseases. Based on this reason, it is important to observe the location and time, where and when, malnutrition in Depok happened in high intensity. To obtain the location and time of the hotspots of malnutrition and diseases that attack children under five years old, space-time scan statistics method can be used. Spacetime scan statistic is a hotspot detection method, where the area and time of information and time are taken into account simultaneously in detecting the hotspots. This method detects a hotspot with a cylindrical scanning window: the cylindrical pedestal describes the area, and the height of cylinder describe the time. Cylinders formed is a hotspot candidate that may occur, which require testing of hypotheses, whether a cylinder can be summed up as a hotspot. Hotspot detection in this study carried out by forming a combination of several variables. Some combination of variables provides hotspot detection results that tend to be the same, so as to form groups (clusters). In the case of infant health level in Depok city, health care center region in is a hotspot. According to the combination of the variables used in the detection of hotspots, health care center is most frequently as a hotspot. Hopefully the local government can take the right policy to improve the health level of children under five in the city of Depok. Keyword: Space-time scan statistic, hotspot, malnutrition, INTRODUCTION Several problems affecting the health in Indonesia, especially in Depok city is the high number of malnutritions among children under five from year to year as well as patients with pneumonia also in this age group (Profil Kesehatan Depok, 2014). Malnutrition is a condition of malnutrition at a level which is already severe, where the nutritional status is far below the standard. Pneumonia is an inflammation of tissue in one or both lungs which is usually caused by infection. At the time suffering from pneumonia, a set of air pockets at the end of the small airways in the lungs will be swollen and full of fluid. Malnutrition and pneumonia is a disease that is very susceptible to the children under five, worse pneumonia and malnutrition can cause death. It is quite alarming as considering children (children under fives) are the future generation. Many things can affect malnutrition and pneumonia include vitamin deficiencies, lack of attention to health. Routine medical eamination plays an important role in terms of improving health. To obtain the location and time of the hotspots of malnutrition, pneumonia and other cases in infants space-time scan statistic method can be used. Scan statistics is a statistical method to detect the hotspot of an event (case) in a study area. Hotspot is a critical area, an area with the highest intercity of event. Space-time scan statistic method takes into account the area and time of information simultaneously in detecting hotspots. In this study, we want to discuss about the hotspot area in Depok on malnutrition, pneumonia and some other things which pertain to children under fives, so the local government can take the appropriate action to reduce the malnutrition and morbidity (ilness rate) of Statistics and its Applications AIP Conf. Proc. 1827, ; doi: / Published by AIP Publishing /$

3 children under five years old in Depok. THE OBJECTIVE The objective in this study is to determine the location and time of the hotspots of malnutrition, pneumonia, weight below the red line and the death cases of a children under five years old using the space-time scan statistic. THEORETICAL BASIS The data in this study is the number of event of interest in a region in a population: An event happens as a counting process. Therefore, the number of event in a region is assumed to make a Poisson distribution and the hotspot detection is based on the Poisson distribution. Poisson Distribution Random variable is said to be the Poisson distribution if it has p.m.f (probability mass function) as follows: Poisson distributed random variables resulting from a Poisson process. Poisson process can be defined as a process that results in a number of changes within a certain interval. A random variable is said to follow the process if they meet the prostulat of poisson process as follows. Let determine the probability of a change within each interval with length Furthermore, suppose declare a function such that as eample and Postulate poisson process are where is a positive constant and, and frequent changes in a separate interval are independent. (Hogg and Craig. 1995) Space-time Scan Statistics Etraordinary event is an event with a higher intensity in a particular area and time. Space-time scan statistic method is used to detect outbreaks at a specific area and time. The eceptional results of event detection is very useful as an early warning. Therefore, the most appropriate approach is a prospective approach. In this study, the event is assumed as a Poisson distribution, and the rate of etraordinary events are assumed constant (persistent). Etraordinary event detection is done by forming a scanning window. For each scanning window formed, calculate the value of ratio likelihood. Space-time cluster (area and time of etraordinary events) is a scanning window with the highest likelihood ratio value which is statistically significant. Maimum Likelihood Estimation Maimum likelihood is a method to estimate an unknown parameter of a function of probability. Suppose is a random variable that has a certain shape of probabilities functions that depend on an unknown parameter, then the probability function of can be written as,, with is the parameter space. Here is the definition of MLE (Maimum Likelihood Estimation). Definition: Let is a random variable that has the form of the probability function The likelihood function is defined as follows: A joint probability function of random variables that depend on. In the maimum likelihood method, a function of, let will be obtained such that if change with, then the value of will maimaze the likelihood function and is called the maimum likelihood estimation (MLE) of (Hogg and Craig, 1995)

4 The Likelihood Ratio Test Likelihood ratio test is a method to test the hypothesis against the alternative hypothesis with is the overall parameter space and is the parameter space on. Let is independent random variables with each of the distribution function is Let is a set that contain all parameter point is called as the parameter space. Let is a subset of the parameter space The hypothesis will be tested, against In this study, observed events are assumed as Poisson distribution with the formation of the test statistic as follows: Pure Spatial Let N denote a spatial point, G denote the study area and Z denote the scanning window. As the scanning window (Z) moves around G, there will be, a collection of. Furthermore,, n(g), n(z) consecutively denote population in G, population in Z, number of case in G, and number of case in Z. The null hypothesis is set to be no significant cluster was generated, i.e., and the alternative hypothesis is there was significant cluster generated, i.e., where is the rate of case inside the scanning window (Z), while is the rate of case outside Z. The likelihood function for the Poisson model is a little more comple. The probability of number of points in the study area is: The density function of a specific point being observed a location is: We can hence write the likelihood function as: As before, the likelihood ratio is defined as in equation 2. We have: (1) For the numerator we first take the supremum over all and for a fied. Equation 3 takes its maimum when and so The test statistics of the likelihood ratio test can now be written as: If there is at least one zone such that 1997) (2) (3) and otherwise. is the indicator function. (Kulldorf,

5 THE DATA AND METHOD The Data This study uses the children under five years old health data from 31 health centers in the city of Depok in years , the variables (indicators) are: the number of children under five suffering from malnutrition, the number of infants suffering from pneumonia, the number of underweight children weight below the red line, the number of infants who did not receive vitamin A, the number of infants who do not get health care and the number of infants who died. The number of observation of this 6 indicators are based on every health center region in every year, aggregately. The Method This purpose of this study is to find hotspots in the case of infant health in the city of Depok at the (area) of health care centers using the space-time scan statistic. The step undertaken in this study are (1) Scanning window formation, (2) Determine the hypothesis and, (3) Test the hypothesis using a likelihood ratio test statistic, (4) Test of significance with Monte-carlo, (5) Determine the decision, whether rejected or not rejected by determining the level of significance. rejected if the p-value < and not rejected if the p-value >. RESULT AND DISCUSSION Depok city geographically located at coordinates 6 19'00"- 6 28'00" latitude and '00" '30" east longitude. Depok city as one of the youngest regions in West Java, has an area of approimately km 2 with a population of 2,033,508 people (BPS Depok, 2014). Depok city consists of 31 health care center regions shown at the following image, Figure 1. FIGURE 1. The Study Area Hotspot of each variable Calculation of hotspot detection is carried out using an open source software, SatScan, and the results are presented using the R open-source software. Here is the result along with brief eplanations related:

6 y FIGURE 2. The Hotspot of Malnutrition: health care center region Figure 2 shows that the hotspot of malnutrition of children under five years old case is in in with the number of cases 386 (p-value < 0.001), the relative risk is 8.50 and the epected number of cases is The hotspot was in the east area of Depok. y FIGURE 3. The Hotspot of Pneumonia: health care center region Figure 3 shows that the hotspot of pneumonia of children under five years old case is in health care center region in with 1042 cases (p-value < 0.001), the relative risk is 8.59 and the epected number is The hotspot was in the central north area of Depok

7 y FIGURE 4. The Hotspot area of Variable Underweight:, Cilangkap, Cilodong,,, Pancoran Mas, Pondok Sukmajaya, Sukmajaya and Villa Pertiwi Heath Care Center Regions Figure 4 shows that the hotspot area of underweight of children under five years old case consists of nine health care center regions in 2011 with 3837 cases (p-value < 0.001), the relative risk is 3.56 and the epected number is The hotspot was in the south area of Depok. y FIGURE 5. The Hotspot Area of Children Under Five Years Old Who Did Not Receive Vitamin A: 14 Health Care Center Regions Figure 5. shows that the hotspot area of children under five years old who did not receive vitamin A consists of 14 health care center regions in 2013 with cases (p-value < 0.001), the relative risk is 2.23 and the epected number is The hotspot was in the west area of Depok

8 y FIGURE 6. The Hotspot Area of Children Under Five Years Old Who Did Not Get Health Care: 13 Health Care Center Regions Figure 6. shows that the hotspot area of children under five years old who did not get health care consists of 13 health care center regions in 2014 with cases (p-value < 0.001), the relative risk is 1.78 and the epected number is The hotspot was in the west area of Depok. y FIGURE 7. The Hotspot Area of The Total Death of Children Under Five Years Old: 11 Health Care Center Regions Figure 7. shows that the hotspot number of death of children under five years old is in any health care center region in 2011 with 78 cases (p-value < 0.001), the relative risk is 3.34 and the epected number is The hotspot was in the south west of Depok. Hotspot of combination of some variables (indicators) Si hotspot areas based on every indicators in this study have been shown in part one of the result. Furthermore, this part shows the result of hotspot areas based on some indicators simultaneously. The objective of this part to obtain

9 the five most severe regions in the hotspot area most often. Combination from si indicators are determined. Table 1 shows the regions and the times it emerged in the hotspot areas. It shows that, Pancoran Mas, Tanah Baru, and Pasir Putih are the most severe in chidren under five health level in Depok. TABLE 1. Ranking of Hotspot in Health Care Center Region in Study Area: Depok Ranking Health Care Center Times Being Hotspot 1 57 of 62 2 Pancoran Mas 56 of 62 3 Tanah Baru 51 of of 62 4 Pasir Putih 49 of of 62 4 Sawangan 49 of 62 5 Rangkapan Jaya Baru 48 of of of 62 7 Duren Seribu 46 of of of 62 9 Pondok Sukmajaya 41 of of of Villa Pertiwi 8 of Cilodong 6 of of Kemiri Muka 6 of of Sukmajaya 6 of of Pasir Gunung Selatan 5 of Cilangkap 4 of of of of of of Cimpaun 0 of 62 The result of the detection of hotspots that appear most frequently on the combination of multiple data sets at the same time and area is the area of health care centers with a total of 57 times emerged as hotspot. CONCLUSION AND RECOMMENDATION Hotspot detection is carried out by observing several groups of observational data based on the number of several variables related to the children under five years old in health care center level and the number of populations size of the region in the city of Depok. Some combinations of variables produce the same region as the result of the hotspot detection, so that the region and the time that often appear in these combinations are designated as the hotspots, that is health care center region occurred in This means that this area has the worst rate of infant health compared to other regions. The Advice can be given on the results of this study are: The results of this detection can be used as a guideline for the local governments or other stakeholders in making decisions for improvement, especially in the health field. For more accurate results this study can be done by adding the patient data from health care center in the city

10 of Depok. This study is useful for the hotspot detection of other study areas or other event of interest who want to know the health condition (or others) in the regions. ACKNOWLEDGMENT This research was funded by Directorate of Research and Community Service of Universitas Indonesia (DRPM UI) as a grant of PITTA (Publikasi Internasional Terindeks Tugas Akhir) REFERENCE 1. Dinas Kesehatan Kota Depok, Profil Kesehatan Kota Depok, Glaz Joseph, Naus Joseph, Wallenstein Sylvan. Scan Statistics Hogg and Craig, Introduction to Mathematical Statistics Prentice Hall: New Jersey 4. Hogg, McKean and Craig. Statistics Mathematic M. Kulldorff, Mostashari F, Duczmal L, Yih K, Kleinman K, Platt R. Multivariate spatial scan statistics for disease surveillance. Statistics in Medicine, 2007, 26: M. Kulldorff. A spatial scan statistic. Communications in Statistics:Theory and Methods, 26(6): , M. Kulldorff and N. Nagarwalla. Spatial disease clusters: detection and inference. Statistics in Medicine, 14: ,