Predictive Policing

UAE is one of the safest countries to live in, but that does not indicate that the country does not witness crimes, During the COVID-19 pandemic, the country saw an increase in cyber and digital crimes. Apart from cybercrime, there are other types of crimes, such as street crimes and violent crimes. Data analytics aids Dubai Police to predict crimes. Criminal investigation is one of the fields that is very interesting and is taught in colleges and academies. Data analytics opens the door for studying the details of each crime. Data mining tools consist of a variety of techniques that can help solve a problem or indicate a cause or an effect of something. Data analysts use data mining tools through a lot of software that allow the user to analyze data easily and fluently. SAS (statistical analysis system) is one of the reputable software that is used especially for visualizing and analyzing data. In this capstone, we will use SAS since it is a software that is accredited from Dubai Police and we use it already in our workplace. Prediction techniques supports to interpret and facilitate Dubai Police to develop strategies to reduce the crime rate. Hence, it allows UAE to sustain its position as the “safest” country. The capstone idea will actually help us develop what we do at work and stop or reduce crime which is one of the main pillars in Dubai Police. The crime related data will be collected from CID in Dubai police. Link analysis and predictive analysis will be performed in this project to forecast any crime. We will build a predictive model using SAS to predict crime. This proposed project will help to identify the trends of historical crime data. Project timeline has been provided in this writing to have a better outline. The first step is to collect the data from the source which is in our case, the criminal investigation department in Dubai Police. Meeting with the department; they have agreed on giving us datasets of specific crimes that Dubai Police finds critical and needs further analysis from five years. Thus, the data that we will be analyzing will be from the years 2017 to the year 2021. After collecting the data ; the processing took place which is the cleaning part of the data. Since the data is in Arabic and it is old as mentioned earlier that the data of the past five years are collected; there are some missing fields, some inconsistencies and some redundant data. After cleaning the dataset which took 70% of the time working on this project. Now the dataset is ready and can be analyzed in SAS. Importing the dataset through SAS was the first step. Then, we started analyzing the criminals first as we wanted to build a portfolio of the criminals and observe of any patterns found. The highest nationality of the criminals was India. We tried to see if there are higher nationalities in certain years, but in all five years the analysis showed that India was the number one nationality in criminals. Then we wanted to observe the criminals’ education level; the highest education level was unemployed meaning they do not have any degree that supports them. The education level part was very interesting because we found out that even though university degrees did not come first in the highest education level. however there is a sample of the criminals that hold very high level degrees such as PhDs and Masters degrees and this shows us that the stereotype of how uneducated people are bad or are the only people that commit crimes should be disregarded. Next , we analyzed the criminals’ age group and the outcome was that 30 – 45 age groups are the ones that commit crimes the most in Dubai. Finally, we have analyzed the criminals’ gender to see which gender commits most crimes in Dubai and from our analysis; the outcome showed that men are the most that commit crimes in Dubai. After analyzing the criminals’ profiles ; we have moved on to analyzing the crimes in the past five years. The type of crime was the first thing we wanted to analyze to observe what is the most crime committed in Dubai in the last five years. Fraud was the most crime committed in Dubai and this was not a huge shock to us since Dubai is considered a business city and it attracts some people to do their business in it. Dubai has always been interested in building the city financially in the best , legal way possible, however there will always be people that see it as a city to commit fraud in since it has a large population and has many tourists visiting the city. Next, we analyzed the crime replotting per year. 2019 has scored the highest in crime reporting in Dubai; right before the pandemic. We analyzed the police stations that had the most reporting in the past five years in order to observe the locations that are considered crime appealing to criminals. This analysis is very important since every area has a police station assigned to it and the outcome of this analysis was that Bur Dubai police station had the highest number of incidents in the last five years. Lastly, we wanted to analyze what time was the crime committed and the result was that most crimes have been committed in the morning between 9AM and 11AM and that was very shocking and interesting to us because it is know globally that most crimes are committed at night in the dark where no one can see the criminal , but this is due to the type of crime as well , and as we have observed that fraud is the most committed crime, then the morning is the best time to commit this crime since people are awake and willing to do business with other people whether it was online or offline. Finally, the purpose of this whole project is to forecast the crime rates; thus, we built a forecasting model in SAS and it showed us that in the upcoming years, the crime rates in Dubai will decrease dramatically based on the pattern of crimes in the historical data. This is a positive result; however this does not mean that Dubai Police should neglect the surveillance and monitoring of the city due to this forecasting as it is not always accurate

A novel strategy for the identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites in closely related bacteria

We devised software tools to systematically investigate the contents and contexts of bacterial tRNA and tmRNA genes, which are known insertion hotspots for genomic islands (GIs). The strategy, based on MAUVE-facilitated multigenome comparisons, was used to examine 87 Escherichia coli MG1655 tRNA and tmRNA genes and their orthologues in E.coli EDL933, E.coli CFT073 and Shigella flexneri Sf301. Our approach identified 49 GIs occupying ∼1.7 Mb that mapped to 18 tRNA genes, missing 2 but identifying a further 30 GIs as compared with Islander [Y. Mantri and K. P. Williams (2004), Nucleic Acids Res., 32, D55–D58]. All these GIs had many strain-specific CDS, anomalous GC contents and/or significant dinucleotide biases, consistent with foreign origins. Our analysis demonstrated marked conservation of sequences flanking both empty tRNA sites and tRNA-associated GIs across all four genomes. Remarkably, there were only 2 upstream and 5 downstream deletions adjacent to the 328 loci investigated. In silico PCR analysis based on conserved flanking regions was also used to interrogate hotspots in another eight completely or partially sequenced E.coli and Shigella genomes. The tools developed are ideal for the analysis of other bacterial species and will lead to in silico and experimental discovery of new genomic islands

MobilomeFINDER: web-based tools for in silico and experimental discovery of bacterial genomic islands

MobilomeFINDER (http://mml.sjtu.edu.cn/MobilomeFINDER) is an interactive online tool that facilitates bacterial genomic island or ‘mobile genome’ (mobilome) discovery; it integrates the ArrayOme and tRNAcc software packages. ArrayOme utilizes a microarray-derived comparative genomic hybridization input data set to generate ‘inferred contigs’ produced by merging adjacent genes classified as ‘present’. Collectively these ‘fragments’ represent a hypothetical ‘microarray-visualized genome (MVG)’. ArrayOme permits recognition of discordances between physical genome and MVG sizes, thereby enabling identification of strains rich in microarray-elusive novel genes. Individual tRNAcc tools facilitate automated identification of genomic islands by comparative analysis of the contents and contexts of tRNA sites and other integration hotspots in closely related sequenced genomes. Accessory tools facilitate design of hotspot-flanking primers for in silico and/or wet-science-based interrogation of cognate loci in unsequenced strains and analysis of islands for features suggestive of foreign origins; island-specific and genome-contextual features are tabulated and represented in schematic and graphical forms. To date we have used MobilomeFINDER to analyse several Enterobacteriaceae, Pseudomonas aeruginosa and Streptococcus suis genomes. MobilomeFINDER enables high-throughput island identification and characterization through increased exploitation of emerging sequence data and PCR-based profiling of unsequenced test strains; subsequent targeted yeast recombination-based capture permits full-length sequencing and detailed functional studies of novel genomic islands

Health in times of uncertainty in the eastern Mediterranean region, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

Background: The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. Methods: GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. Findings: The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100 000 people), which increased by 17·2% since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100 000 people) in 2013, which decreased by 26·9% since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3% since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60–80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7% to 7·5% between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred. Interpretation: Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts

Health in times of uncertainty in the eastern Mediterranean region, 1990�2013: a systematic analysis for the Global Burden of Disease Study 2013

Background The eastern Mediterranean region is comprised of 22 countries: Afghanistan, Bahrain, Djibouti, Egypt, Iran, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Pakistan, Palestine, Qatar, Saudi Arabia, Somalia, Sudan, Syria, Tunisia, the United Arab Emirates, and Yemen. Since our Global Burden of Disease Study 2010 (GBD 2010), the region has faced unrest as a result of revolutions, wars, and the so-called Arab uprisings. The objective of this study was to present the burden of diseases, injuries, and risk factors in the eastern Mediterranean region as of 2013. Methods GBD 2013 includes an annual assessment covering 188 countries from 1990 to 2013. The study covers 306 diseases and injuries, 1233 sequelae, and 79 risk factors. Our GBD 2013 analyses included the addition of new data through updated systematic reviews and through the contribution of unpublished data sources from collaborators, an updated version of modelling software, and several improvements in our methods. In this systematic analysis, we use data from GBD 2013 to analyse the burden of disease and injuries in the eastern Mediterranean region specifically. Findings The leading cause of death in the region in 2013 was ischaemic heart disease (90·3 deaths per 100�000 people), which increased by 17·2 since 1990. However, diarrhoeal diseases were the leading cause of death in Somalia (186·7 deaths per 100�000 people) in 2013, which decreased by 26·9 since 1990. The leading cause of disability-adjusted life-years (DALYs) was ischaemic heart disease for males and lower respiratory infection for females. High blood pressure was the leading risk factor for DALYs in 2013, with an increase of 83·3 since 1990. Risk factors for DALYs varied by country. In low-income countries, childhood wasting was the leading cause of DALYs in Afghanistan, Somalia, and Yemen, whereas unsafe sex was the leading cause in Djibouti. Non-communicable risk factors were the leading cause of DALYs in high-income and middle-income countries in the region. DALY risk factors varied by age, with child and maternal malnutrition affecting the younger age groups (aged 28 days to 4 years), whereas high bodyweight and systolic blood pressure affected older people (aged 60�80 years). The proportion of DALYs attributed to high body-mass index increased from 3·7 to 7·5 between 1990 and 2013. Burden of mental health problems and drug use increased. Most increases in DALYs, especially from non-communicable diseases, were due to population growth. The crises in Egypt, Yemen, Libya, and Syria have resulted in a reduction in life expectancy; life expectancy in Syria would have been 5 years higher than that recorded for females and 6 years higher for males had the crisis not occurred. Interpretation Our study shows that the eastern Mediterranean region is going through a crucial health phase. The Arab uprisings and the wars that followed, coupled with ageing and population growth, will have a major impact on the region's health and resources. The region has historically seen improvements in life expectancy and other health indicators, even under stress. However, the current situation will cause deteriorating health conditions for many countries and for many years and will have an impact on the region and the rest of the world. Based on our findings, we call for increased investment in health in the region in addition to reducing the conflicts. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Genomic diversity of ten Escherichia coli strains associated with bloodstream infections.

Escherichia coli are usually regarded as a harmless human colonic flora. However, pathogenic strains of E. coli have been associated with infections that could range from infected mucosal surfaces by intestinal pathogenic E. coli to the more severe cases of disseminated infections throughout the body by the extraintestinal pathogroups. The main focus of this project was to investigate the genomic contents of pathogenic bloodstream infection (BSI)-associated E. coli strains. This is because the genome contents of the E. coli BSI-associated isolates have not been well studied, with only few reports indicating that the pathogenincity of these strains could be attributed to horizontally acquired DNAs known as genomic islands (GEIs). The genomic contents of 10 clinical BSI-associated E. coli strains, isolated at the Leicester Royal Infirmary were investigated in this study. The first approach used to investigate the genomic contents of these strains was by interrogating the downstream ends of tRNA genes for their GEI contents by the sequential PCR strategy tRIP-PCR (tRNA interrogation for pathogenicity islands) followed by the SGSP-PCR (single genome specific primer-PCR). In this approach the flanking regions of the tRNA sites were used to first screen the tRNA genes for their GEIs followed by amplifying the boundaries of the identified GEIs. In the second approach termed Microarray-Assisted mobilome Prospecting (MAmP), the physical genome size of the tested strains obtained by the pulsed-field gel electrophoresis (PFGE) is compared to the sum total of the bits of the genome detected or visualized by the array. The difference between the two measurements is used to estimate the size of the novel, non-microarray-represented mobile genome (mobilome) present in the tested strains. Remarkably, despite only studying 10 E. coli strains, associated with a single disease type the tRIP-PCR method has identified at least 3 GEIs that contain novel sequences, and 46 GEIs, resembling uropathogenic E. coli CFT073-like entities. One particular strain E105 had 13 tRNA sites occupied with GEIs. On the other hand, an average novel, non-microarray-borne mobilome of (219 kb /strain) was obtained by the MAmP which, corresponds with previous studies. The strategies used in this study had proved successful in addressing and identifying mobilome-rich strains. Therefore, using such approaches in combination with whole genome sequencing progects could prioritize the strains and the genomic regions that need to be sequenced. Such prioritization would avoid sequencing of hundreds of isolates to identify their novel gene pool and would reduce the cost of genomic sequencing. Moreover, applying such approaches for the identification of new virulence genes and/or pathogenic mechanisms could lead to significant improvements in the treatment of E. coli infections

Genomic diversity of ten Escherichia coli strains associated with bloodstream infections

Escherichia coli are usually regarded as a harmless human colonic flora. However, pathogenic strains of E. coli have been associated with infections that could range from infected mucosal surfaces by intestinal pathogenic E. coli to the more severe cases of disseminated infections throughout the body by the extraintestinal pathogroups. The main focus of this project was to investigate the genomic contents of pathogenic bloodstream infection (BSI)-associated E. coli strains. This is because the genome contents of the E. coli BSI-associated isolates have not been well studied, with only few reports indicating that the pathogenincity of these strains could be attributed to horizontally acquired DNAs known as genomic islands (GEIs). The genomic contents of 10 clinical BSI-associated E. coli strains, isolated at the Leicester Royal Infirmary were investigated in this study. The first approach used to investigate the genomic contents of these strains was by interrogating the downstream ends of tRNA genes for their GEI contents by the sequential PCR strategy tRIP-PCR (tRNA interrogation for pathogenicity islands) followed by the SGSP-PCR (single genome specific primer-PCR). In this approach the flanking regions of the tRNA sites were used to first screen the tRNA genes for their GEIs followed by amplifying the boundaries of the identified GEIs. In the second approach termed Microarray-Assisted mobilome Prospecting (MAmP), the physical genome size of the tested strains obtained by the pulsed-field gel electrophoresis (PFGE) is compared to the sum total of the bits of the genome detected or visualized by the array. The difference between the two measurements is used to estimate the size of the novel, non-microarray-represented mobile genome (mobilome) present in the tested strains. Remarkably, despite only studying 10 E. coli strains, associated with a single disease type the tRIP-PCR method has identified at least 3 GEIs that contain novel sequences, and 46 GEIs, resembling uropathogenic E. coli CFT073-like entities. One particular strain E105 had 13 tRNA sites occupied with GEIs. On the other hand, an average novel, non-microarray-borne mobilome of (219 kb /strain) was obtained by the MAmP which, corresponds with previous studies. The strategies used in this study had proved successful in addressing and identifying mobilome-rich strains. Therefore, using such approaches in combination with whole genome sequencing progects could prioritize the strains and the genomic regions that need to be sequenced. Such prioritization would avoid sequencing of hundreds of isolates to identify their novel gene pool and would reduce the cost of genomic sequencing. Moreover, applying such approaches for the identification of new virulence genes and/or pathogenic mechanisms could lead to significant improvements in the treatment of E. coli infections.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A Retrospective Epidemiological Study of the Incidence and Risk Factors of Salmonellosis in Bahrain in Children during 2012–2016

Salmonellosis is one of the major public health concerns in Bahrain as it has increased rapidly during the past few years. This study aims to determine the prevalence of salmonellosis in children and the possible risk factors such as age, geographical area, nationality, gender, unsafe drinking water, infant born weight and gastrointestinal disease. The cases of salmonellosis in children reported by the Ministry of Health of Bahrain ranged from 21 to 26 per 100,000 population during the period 2012–2016. Salmonellosis cases were geographically concentrated in the capital and northern regions. Statistical analysis showed a significant difference in the number of salmonellosis cases between Bahrainis and non-Bahrainis based on region, and gender (p < 0.001). In the Bahraini cohort, there was an association between the increase of cases and the number of gastrointestinal disease-related deaths (p < 0.05). In addition, unsafe water (over the level of 2.14%) and low-birth weight (<3.100 g) were associated, but not statistically significant (p = 0.086 and p = 0.126, respectively) with the increase of salmonellosis cases. Despite the decline in the number of cases, the results of this study contribute to the understanding of the epidemiology of Salmonella in humans and this, in turn, will help develop and implement preventative measures

Excessive iodine status among school‐aged children in the State of Qatar: Results of the National Iodine Deficiency Disorder Survey

Abstract Background Iodine deficiency poses a significant public health challenge worldwide, particularly in preschool children and pregnant women. Assessing the iodine intake at a population level is essential, as both deficient and excessive iodine status can have adverse health consequences. The main objective of this survey is to understand the iodine deficiency status in schoolchildren aged 6–12 years in the State of Qatar. Methods A cross‐sectional survey was conducted from March to June 2014 among school‐aged children using a two‐stage cluster sampling technique. Anthropometric, biochemical, clinical, and dietary parameters for seafood were collected. Spot urine samples were collected from 967 participants, and a repeat random subsample urine was collected from 288 participants. Overall median urinary iodine concentration (UIC) was calculated. Iodine content in household salt samples was estimated by qualitative and quantitative methods. Mann–Whitney U test was used for comparison. Results The median UIC was 333.2 μg/L (IQR = 228.6). UIC prevalence rates between 300–999 and >1000 μg/L were 56.7% and 2.8%, respectively. The goiter prevalence was 0.4%. A significant difference was noted in overall median UIC levels between boys and girls (p = 0.003). Adequate iodized salt consumption was reported by 74.9% of households, and weekly seafood consumption was reported by one third of the respondents. Conclusion The results indicate an excess intake of iodine among the studied population in the State of Qatar, and national efforts are needed to bring iodine intake and concentration levels within the cutoff value for the concerned survey population's age group. In addition, a surveillance system needs to be set up for continuous monitoring of iodine content and salt intake at the population level in the State of Qatar