Determinants of the Underlying Causes of Mortality during the First Wave of...

[Full title: Determinants of the Underlying Causes of Mortality during the First Wave of COVID-19 Pandemic in Saudi Arabia: A Descriptive National Study]

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International Journal of Environmental Research and Public Health Article Determinants of the Underlying Causes of Mortality during the First Wave of COVID-19 Pandemic in Saudi Arabia: A Descriptive National Study Abdullah M. Asiri 1 , Shaker A. Alomary 2 , Saeed A. Alqahtani 2 , Izzeldin F. Adam 2,3 and Samar A. Amer 2,4, * Citation: Asiri, A.M.; Alomary, S.A.; Alqahtani, S.A.; Adam, I.F.; Amer, S.A. Determinants of the Underlying Causes of Mortality during the First Wave of COVID-19 Pandemic in Saudi Arabia: A Descriptive National Study Int. J. Environ. Res. Public Health 2021 , 18 , 12647. https:// doi.org/10.3390/ijerph 182312647 Academic Editor: Giuseppe Biondi Zoccai Received: 10 October 2021 Accepted: 18 November 2021 Published: 30 November 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations Copyright: © 2021 by the authors Licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/) 1 Department of Infectious Diseases, Preventive Health, Ministry of Health, Riyadh 11176, Saudi Arabia; abdullahm.asiri@moh.gov.sa 2 Department of Health Programs and Chronic Diseases, Ministry of Health, Riyadh 11176, Saudi Arabia; Shalomary@moh.gov.sa (S.A.A.); Sahalqahtani@moh.gov.sa (S.A.A.); iabdellah@moh.gov.sa (I.F.A.) 3 Department of Epidemiology, University of Khartoum, Khartoum 11115, Sudan 4 Department of Public Health and Community Medicine, Zagazig University, Zagazig 44519, Egypt * Correspondence: amers@moh.gov.sa Abstract: Since the emergence of the COVID-19 pandemic, the mortality statistics are constantly changing globally. Mortality statistics analysis has vital implications to implement evidence-based policy recommendations. This study aims to study the demographic characteristics, patterns, determinants, and the main causes of death during the first half of 2020, in the Kingdom of Saudi Arabia (KSA). Methodology: A retrospective descriptive study targeted all death (29,291) registered in 286 private and governmental health settings, from all over KSA. The data was extracted from the ministry of health’s death records after the ethical approval. The International Classification of Diseases (ICD-10) and WHO grouping, were used to classify the underlying causes of deaths. The collected data were analyzed using the appropriate tables and graphs. Results: 7055 (24.9%) died at the middle age (40–59 year), and 19,212 (65.6%) were males, and 18,110 (61.8%) were Saudi. The leading causes of deaths were non-communicable diseases (NCDs) 15,340 (62.1%), mainly Cardiovascular diseases (CVDs) 10,103 (34.5%). There was a significant relationship between the main causes of deaths and sex ( p < 0.05) and nationality ( p = 0.01). Conclusion: NCDs mainly CVDs are the leading cause of death. The COVID-19 mortalities were mainly in males, and old age > 55 year. The lockdown was associated with a reduction in the NCDs and Road traffic accidents mortalities Keywords: COVID-19; international classification of diseases; Kingdom of Saudi Arabia; underlying mortality 1. Introduction World Health Organization (WHO), On 19 March 2020, declared COVID-19 as a pandemic [ 1 ]. It becomes one of the deadliest pandemics in the last century [ 2 ]. Worldwide, On, 20 July 2020, the deaths have already exceeded 609,000. While in the Kingdome of Saudi Arabia (KSA), there were 2486 deaths to be on the 27 th rank according to the number of deaths [ 3 ]. COVID-19 pandemic affects the entire health system resulting in potentially unexpected worse health outcomes and increases the overall mortality [ 4 , 5 ]. The interaction between COVID-19 and NCDs may increase the global burden of disease (GBD) [ 6 ]. Globally, NCDs, are responsible for two out of every three deaths [ 7 ] and from all deaths accounted for greater than 70% in 2017 [ 8 ] and approximately 73% with more than 90,000 deaths per year in KSA [ 9 ]. NCDs deaths are mainly due to cardiovascular diseases (CVDs), cancers, chronic respiratory diseases, and diabetes [ 10 – 12 ]; other major causes include suicide and injury [ 13 ]. Int. J. Environ. Res. Public Health 2021 , 18 , 12647. https://doi.org/10.3390/ijerph 182312647 https://www.mdpi.com/journal/ijerph

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 2 of 16 Mortality data derived from death certificates are used to measure the population health and to compare mortalities at the national and international levels [ 14 ]. It reflects the social, economic, environmental conditions and the provided health care [ 15 , 16 ]. The determinants of mortality facilitate the planning and evaluation of health policies and programs. The mortality trends highlight the urgency of adapting health systems to better meet the changing healthcare needs, by improving the capacity to prevent and manage NCDs [ 6 ] because the disease progress is not uniform continuously changes [ 16 ]. Therefore, the reported trends can be incorporated into the adaptation process Mortality indices should be a part of the country system backbone continuously, as important health care quality markers, provide essential inputs for national and subnational health policy and planning [ 7 ], and help in predicting and evaluating many disease prevention initiatives and health promotion programs [ 17 ]. The scientific information available on the status and trends of various Communicable Diseases (CDs), NCDs, and deaths are limited to the primary statistics available in the portals of the Ministry of Health (MOH) and other health agencies [ 18 ]. However, studies on these available data in KSA are scanty and scattered. Although KSA is the largest Arab state in Western Asia and is part of the “Group of Twenty” (G-20) of major economies [ 19 ], it still requires accurate and comprehensive relevant national health data Hence, the present study aimed; to provide relevant national-based mortality statistics to guide the government and policymakers for the optimal resources allocation to enhancing life expectancy and reducing mortality in KSA. The study attempted to determine the demographic characteristic, patterns, determinants, and underlying causes of mortality during the first half of 2020 during the first wave of COVID-19 pandemic in KSA 2. Methodology 2.1. Participants A retrospective descriptive study, from 1 January until the end of June 2020. Record based study targeted all the registered mortalities from 286 health settings {governmental hospitals (85.0%), medical cities (5.0%), governmental health centers (5.0%), private hospitals (4.0%) and specialized governmental hospitals (1.0%)} all over the 20 health regions in KSA 2.2. Data Collection Extracted data about three main parts: demographic data (age, sex, and nationality), mortality data include (date of death, the underlying cause of death coded using the ICD-10), and the regions The causes of death are classified according to The International Classification of Diseases (ICD-10) [ 20 ] and WHO classification [ 21 ] We reassigned deaths with ill-defined or codes to be allocated to other causes using previously published methods as described by Mathers et al. [ 22 ], e.g., cancers of the unspecified site to cancer, ill-defined cardiovascular causes of death to cardiovascular causes of death. Finally, we redistributed ill-defined causes of death data to all non-injury causes of death 2.3. Statistical Analysis The collected data was coded and analyzed using SPSS (version 22). At a level of significance ( p -value ≤ 0.05) and calculating the following rates. Mortality Rates were calculated using the WHO reference population [ 21 ] and the Mortality was projected using methods applied in other studies [ 23 , 24 ]. 3. Results Out of the 31,509 deaths in KSA during the first half of 2020, the causes of death were available for 29,291 (92%). They were 7055 (24.9%) were middle-aged (40–59 year), and 19,212 (65.6%) were males, and 18,110 (61.8%) were Citizens.

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 3 of 16 According to the ICD-10 classification, the underlying categories of morality in descending order were 6864 (23.4%) CVDs, 2773 (9.4%) ill-defined injury conditions, 2438 (8.3%) infectious and parasitic diseases, 1421 (4.9%) injuries and poisoning, 1199 (4.1%) cancer, 1153 (3.9%) chronic respiratory disorders, 994 (3.4%) RTTA, 864 (2.9%) Acute Respiratory Infections (ARIs), 658 (2.2%) and diabetes, 640 (2.2) (Table 1 ). Table 1. Causes of deaths according to The International Classification of Diseases (ICD-10 codes) in KSA from first of January until 30 June 2020 Diseases and Injury Categories and ICD-10 Codes Underlying Causes F (%) F % I-Communicable diseases (CDs), maternal, and neonatal conditions A-Infectious, parasitic diseases 2438 (8.3) 5141 (17.6) B-Acute Respiratory Infections 864 (2.9) C-Maternal Conditions 177 (0.6) D-Neonatal Causes 351 (1.2) E-Nutritional deficiencies 13 (0.0) • COVID-19 as the cause of disease classified to other chapters 1298 (4.4) II-Non Communicable diseases (NCDs) F-Malignant + other neoplasms 1199 (4.1) 11,862 (40.5) G-Diabetes Mellitus 658 (2.2) H-Endocrine and metabolic disorders 232 (0.8) I-Mental disorders 38 (0.1) J-Nervous System, Sense organ disorders 640 (2.2) K-Cardiovascular Diseases (CVD) 6864 (23.4) L-Chronic Respiratory diseases 1153 (3.9) M-Diseases of the digestive system + Oral health 255 (0.9) N-Genitourinary diseases 483 (1.6) O-Skin diseases 29 (0.1) P-Musculoskeletal disease 96 (0.3) Q-Congenital anomalies 189 (0.6) R-Ill -defined conditions 26 (0.1) III-Injuries S-Unintentional injuries T = 2773 (9.4) 10,213 (34.9) • Road traffic+ other transport accidents 994 (3.4) • Unintentional injuries 184 (0.6) • Injury, poisoning, and certain other consequences of external causes 1421 (4.9) T-Intentional injuries 174 (0.6) U-Codes allocated or redistributed to other codes T = 3071 (10.5) • Ill-defined malignant neoplasm + Unspecified uterine cancer 146 (0.5) • Ill-defined unintended accidents 48 (0.2) • Falls, Burn, Poisoning, Drowning, Suffocation 22 (0.1) • Ill-defined cardiovascular conditions +heart failure 2768 (9.5) • Ill-defined gastrointestinal conditions 87 (0.3)

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 4 of 16 Table 1. Cont Diseases and Injury Categories and ICD-10 Codes Underlying Causes F (%) F % Ill-defined conditions; T = 4369 (14.9%) 10,213 (34.9) • Senility 192 (0.7) • Sudden death 399 (1.4) • Unknown, nonspecific cause of morbidity 114 (0.4) • Instantaneous death 469 (1.6) • Death < 24 h 253 (0.9) • Unattended death 1083 (3.7) • Other ill-defined cause of Mortality 949 (3.2) • Other CVD conditions (abnormal rhythm, blood pressure, and strokes) 471 (1.6) • Others 439 (1.6) IV-Codes of special Conditions • SARS 15 (0.1) 473 (1.6) • Emergency use of U 07.1 [COVID-19, virus identified] 390 (1.3) • Emergency use of U 07.2 [COVID-19, virus not identified] 51 (0.2) • Firearm +Horse race +hyperactivity 17 (0.1) V-Factors that influence the health status 117 (0.4) 117 (0.4) Null 1485 (5.0) 1485 (5.0) Total 29,291 100.0 We found that the main CDs underlying causes of mortalities based on ICD-10 (20) were 3317 (11.3%), out of them 167 (5.0) Streptococcal infection, 95 (2.9%) Varicella 90 (2.7%), 78(2.4%) Mycoplasma Pneumonia, 56 (1. 7%) Tuberculosis (TB), and 42 (1.3%) Hepatitis Table 2 shows that according to ICD-10 and WHO grouping the top leading underlying causes of mortalities in descending orders were NCDs 15,340 (62.1%) including CVDs 10,103 (34.5%), {Communicable, maternal, and perinatal 5546 (18.9)}, Ill-defined causes 4060(13.9%), and Injuries 2860 (9.8%) Table 2. Main underlying causes of mortality from 1 January–30 June 2020 in KSA according to ICD-10 categorization and WHO classification WHO Classification of Main Causes of Deaths The First Half of 2020 Underlying Causes of Mortality F(%) Communicable, maternal, perinatal, and nutritional conditions 5546 (18.9) (including SARS, and COVID-19 confirmed cases by special codes) Diabetes Mellitus 658 (2.2) Chronic Respiratory diseases 1053 (3.9) Cardio-vascular diseases {ICD-10, heart Failure-ill-defined and unspecific Cardiovascular conditions+ heart failure + abnormal heart rhythm+ abnormal blood pressure} 10,103 (34.5)

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 5 of 16 Table 2. Cont WHO Classification of Main Causes of Deaths The First Half of 2020 Underlying Causes of Mortality F(%) Cancer (Malignant+ other neoplasm + Ill-defined malignant neoplasm + Unspecified uterine cancer) 1345 (4.6) Other Non-communicable diseases (NCDs) 2181 (7.4) Injuries • Other Injuries • Road traffic+ other transport accidents 1866 (6.4) 994 (3.4) T = 2860 (9.8%) Ill-defined injury conditions /unknown/risk factors 4060 (13.9) Null 1485 (5.0) No of deaths 29,291 Total no of the population (1440 h, 2019 G) 34,218,168 The national lockdown precautions across months as described in detail as illustrated in (Figure 1 ), the pattern and the total number of mortalities including mortalities of NCDs and RTTA decreased but COVID-19 deaths progressively increased (Figure 2 ). Figure 1. The flow of governmental restriction measures against COVID-19 in KSA, 2020.

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 6 of 16 Int. J. Environ. Res. Public Health 2021 , 182 , 2647 6 of 16 Figure 2. The pattern of the Mortality from the 1 January–30 June 2020 in KSA across months considering the governmental restriction procedures. Analyzing the trends of the main causes of death across months reveals a major shift in the main causes of deaths. As CDs showed a progressive increase from 617 (10.8%) at the end of January to 717 (18.5%) at the end of April, to be 1620 (26.1%) at the end of June. While RTTA and NCDs showed a manifest decrease from 238 (4.1%), 3019(53.2%) reciprocally at the end of January to be 114 (1.9%), and 2146 (55.4%) at the end of April then gradually increased to be 147 (2.4%), and 2894 (47.0%) at the end of June. respectively depicting how drastic the percentages and burden have changed (Figure 2). COVID-19 age-specific mortality rate was less than 2/100,000 population at the age groups <35 year, and progressively increased to be 17.7/100,000 at the age group(50–54 year) then progressively increases till reaching the peak 74.9/100,000 at the age 80 year and more. While CDs other than COVID-19 mortality was 8.4/100,000 at the age group 0– 4 year then stated a progressive increase from 17.7/10 ， 000 at the age of 55–59 year until reach the highest of 529.5/100,000 at the age 80 year and more (Table 3). Table 3. Distribution of the main underlying causes of mortalities by age groups. Age Groups (y) Total Number (f) Proportion al Mortality (%) NCDs Mortality F (%) NCDs-Age Specific ASMR * CDs ** Mortality F (%) CDs- ASMR * COVID -19 Mortality F (%) COVID -19 ASMR * Abortion ------ -------- ----- • <16 w 47 0.2 0 0 (0.0) 0 (0.0) 0 (0.0) • >16 w 236 0.8 23 (0.1) 3 (0.1) 1 m 645 2.2 314 (2.0) 744 26.4 101 (3.04) 236 8.4 1 (0.1) 3 0.01 1 m–12 m 225 0.9 69 (0.4) 14 (0.4) ---- 1–4 776 2.6 361 (2.3) 121 (3.6) 2 (0.1) 5–9 225 0.8 115 (0.7) 3.8 19 (8.4) 0.64 0 --- 10–14 227 0.8 97 (0.6) 3.7 21 (0.6) 0.8 0 ---- 15–19 514 1.8 163 (1.1) 6.9 34 (1.0) 1.4 3 (0.2) 0.13 5679 4843 4351 3877 4382 6159 3019 2658 2412 2146 2211 2894 617 567 541 717 943 1620 238 205 183 114 107 147 0 1000 2000 3000 4000 5000 6000 7000 JA N F EB MAR A PRIL MAY J UNE Total deaths Deaths from non communicable diseaes Deaths from communicable diseaes Death from road traffic + other transport accident Figure 2. The pattern of the Mortality from the 1 January–30 June 2020 in KSA across months considering the governmental restriction procedures Analyzing the trends of the main causes of death across months reveals a major shift in the main causes of deaths. As CDs showed a progressive increase from 617 (10.8%) at the end of January to 717 (18.5%) at the end of April, to be 1620 (26.1%) at the end of June. While RTTA and NCDs showed a manifest decrease from 238 (4.1%), 3019 (53.2%) reciprocally at the end of January to be 114 (1.9%), and 2146 (55.4%) at the end of April then gradually increased to be 147 (2.4%), and 2894 (47.0%) at the end of June. respectively depicting how drastic the percentages and burden have changed (Figure 2 ). COVID-19 age-specific mortality rate was less than 2/100,000 population at the age groups <35 year, and progressively increased to be 17.7/100,000 at the age group (50–54 year) then progressively increases till reaching the peak 74.9/100,000 at the age 80 year and more. While CDs other than COVID-19 mortality was 8.4/100,000 at the age group 0–4 year then stated a progressive increase from 17.7/10,000 at the age of 55–59 year until reach the highest of 529.5/100,000 at the age 80 year and more (Table 3 ). Table 3. Distribution of the main underlying causes of mortalities by age groups Age Groups (y) Total Number (f) Proportional Mortality (%) NCDs Mortality F (%) NCDs-Age Specific ASMR * CDs ** Mortality F (%) CDs-ASMR * COVID-19 Mortality F (%) COVID-19 ASMR * Abortion —— ——– —– • <16 w 47 0.2 0 0 (0.0) 0 (0.0) • >16 w 236 0.8 23 (0.1) 3 (0.1) 0 (0.0) 1 m 645 2.2 314 (2.0) 744 26.4 101 (3.04) 236 8.4 1 (0.1) 3 0.01 1 m–12 m 225 0.9 69 (0.4) 14 (0.4) —- 1–4 776 2.6 361 (2.3) 121 (3.6) 2 (0.1) 5–9 225 0.8 115 (0.7) 3.8 19 (8.4) 0.64 0 — 10–14 227 0.8 97 (0.6) 3.7 21 (0.6) 0.8 0 —- 15–19 514 1.8 163 (1.1) 6.9 34 (1.0) 1.4 3 (0.2) 0.13 20–24 850 2.9 216 (1.4) 8.2 49 (1.5) 1.9 9 (0.5) 0.34

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 7 of 16 Table 3. Cont Age Groups (y) Total Number (f) Proportional Mortality (%) NCDs Mortality F (%) NCDs-Age Specific ASMR * CDs ** Mortality F (%) CDs-ASMR * COVID-19 Mortality F (%) COVID-19 ASMR * 25–29 1049 3.6 343 (2.2) 10.5 75 (2.3) 2.3 20 (1.2) 0.61 30–34 1107 3.8 424 (2.7) 12.9 78 (2.4) 2.4 49 (2.9) 1.48 35–39 1119 3.8 481 (3.1) 12.97 82 (2.5) 2.2 84 (4.9) 2.27 40–44 1361 4.6 666 (4.3) 20.1 96 (2.9) 2.9 146 (8.6) 4.49 45–49 1504 5.1 723 (4.7) 29.3 131 (3.9) 5.3 150 (8.8) 6.9 50–54 2019 6.9 1067 (6.9) 62.23 173 (5.2) 10.1 245 (14.5) 14.28 55–59 2177 7.4 1195 (7.7) 100.9 210 (6.3) 17.7 209 (12.4) 17.66 60–64 2689 9.2 1505 (9.8) 193.2 286 (8.6) 36.7 229 (13.6) 29.39 65–69 2222 7.6 1296 (8.3) 298.7 254 (7.7) 58.6 177 (10.5) 40.87 70–74 2225 7.6 1364 (8.8) 473.5 292 (8.8) 101.4 108 (6.4) 37.5 75–79 2375 8.1 1451 (9.4) 839.5 353 (10.6) 204.2 103 (6.1) 59.6 80–84 2148 7.3 1338 (8.7) 3267 1597.7 333 (10.04) 1104 529.5 69 (4.1) 153 74.8 85–89 1692 5.8 1033 (6.6) 267 (8.0) 48 (2.8) 90–94 1054 3.6 629 (4.1) 176 (5.3) 25 (1.5) 95–99 447 1.5 77 (0.4) 273 (8.2) 8 (0.5) 100–104 208 0.7 128 (0.8) 35 (1.1) 2 (0.1) 105–109 82 0.3 41 (0.3) 16 (0.5) 1 (0.1) 110 or more 38 0.1 21 (0.1) 4 (0.1) —- Total 29,291 100.0 15,430 3317 1688 W = week m = month * Age-Specific Mortality Rates are * by 100,000. ** CDs communicable diseases other than COVID-19 The top regions regarding NCDs mortalities were Al-Ahasa, Jeddah, Riyadh, and Makkah, by 553 (70.5%), 2620 (17.1 %), 2021 (13.2%), and 1936 (12.6%). The lowest was in Al-Qurayyat 92 (0.6%). While the top regions regarding RTTA mortalities are Riyadh, Makkah, Jeddah, and Asser by 23.3%, 9.3%, 7.8%, and 7.4% reciprocal and the lowest was in Al Jouf (0.4%) (Table 4 ). Table 4. Distribution of the main underlying causes of mortality according to the health Provinces in KSA Health Province No of Deaths Proportional Mortality (PM) Province Specific MR% * 10,000 NCDs Proportional Mortality F (%) NCDs- Province Specific MR * 10,000 RTTA Proportional Mortality F (%) RTTA Region- Specific MR * 100,000 Makkah 4270 14.6 17.4 1936 (12.6) 8.2 92 (9.3) 3.7 Riyadh 5271 18.0 6.1 2021 (13.2) 5.5 232 (23.3) 2.7 Jeddah 3616 12.3 7.3 2620 (17.1) 5.3 78 (7.8) 1.6 Al Madinah-Al Monawarah 2355 8.0 10.5 976 (6.4) 4.3 57 (5.7) 2.5 Aseer 1856 6.2 9.76 1010 (6.6) 5.3 74 (7.4) 3.9 Jazan 2151 7.3 13.1 1257 (8.8) 7.6 57 (5.7) 3.4 Al-Qassem 1280 4.4 8.6 573 (3.7) 3.9 18 (1.8) 1.2 Al Taif 1290 4.4 9.48 683 (4.5) 5.2 44 (4.4) 3.3 Eastern Region 1760 6.0 5.17 896 (5.8) 2.6 66 (6.6) 1.9 Tabouk 714 2.4 7.5 314 (2.0) 3.3 52 (5.2) 5.4 Hail 673 2.3 9.2 — 65 (6.5) 8.8 Al-Qunfudah 386 1.3 11.9 270 (1.8) 8.3 10 (1.0) 3.1 Najran 552 1.9 9.07 308 (2.0) 9.1 30 (3.0) 4.9

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 8 of 16 Table 4. Cont Health Province No of Deaths Proportional Mortality (PM) Province Specific MR% * 10,000 NCDs Proportional Mortality F (%) NCDs- Province Specific MR * 10,000 RTTA Proportional Mortality F (%) RTTA Region- Specific MR * 100,000 Al-Jouf 471 1.6 13.3 317 (1.8) 8.9 4 (0.4) 1.1 Al-Ahsa 784 2.7 6.1 553 (70.5) 4.3 27 (2.7) 2.1 Al-Bahaa 486 1.7 9.8 309 (2.0) 6.2 2 (0.2) 0.4 Bisha 399 1.4 9.8 290 (1.9) 7.1 6 (0.6) 1.5 Northern Border 435 1.5 11.3 270 (1.8) 7.0 6 (0.6) 1.6 Hafr -Al Baten 385 1.3 8.2 224 (1.5) 4.7 24 (2.4) 5.1 Al - Qurayyat 157 0.5 8.8 92 (0.6) 5.2 10 (1.0 5.6 * Saudi Statistical book, 2019 (used for the dominator) In KSA, 19,212 (65.6%) of mortalities were males but the SSMR was nearly equal in both sexes. NCDs were the main cause of mortalities in both sexes. There was a statistically significant relationship between the sex and nationalities and main causes of deaths as the Proportional mortalities per sex from COVID-19 more in males 1361(7.1%) but from NCDs more in females 5916 (58.7%) (Tables 5 and 6 ). Table 5. Distribution of the main underlying causes of mortalities according to sex Sex-Specific Mortality Rate (MR) * 100,000 Proportional NCDs Mortality Per Sex F (%) NCDs Sex-Specific MR(SSMR) * 100,000 CDs Proportional MR Per Sex CDs SSMR * 100,000 Proportional COVID-19 Mortality Per Sex F(%) COVID-19 SSMR * 100,000 Sex Males (19,212) 97.9 9424 (49.1) 47.7 1899 (9.8) 9.8 1361 (7.1) 6.9 Females(10,079) 95.8 5916 (58.7) 40.8 1418 (14.1) 100.1 327 (3.2) 2.5 * Saudi Statistical book, 2019 Table 6. The relationship between the main underlying causes of deaths and sex and nationality in KSA Sex Nationality Males N = 19,212 F (%) Females N = 10,079 F (%) Saudi N = 18,110 F (%) Non-Saudi N= 11,181 F (%) Null (N = 1485) 938 (4.9) 547 (5.4) 793 (4.4) 692 (6.2) RTTA (N = 994) 867 (4.5) 127 (1.3) 640 (3.5) 354 (3.2) CDs ***(N = 3317) 1899 (9.9) 1418 (14.0) 2409 (13.3) 908 (8.1)) NCDs (N = 15,340) 9424 (49.1) 5916 (58.7) 10,394 (57.4) 4946 (44.2) COVID-19 (N = 1688) 1361 (7.1) 327 (3.2) 463 (2.6) 1225 (11.0) Other causes ** 4723 (24.7) 1744 (17.3) 3411 (18.8) 3056 (27.3) p 0.01 * 0.00 * * p < 0.05—there was a significant difference; ** includes (Other injuries, ill-defined conditions of injury, factors related to the health service, maternal and neonatal causes); *** CDs—Communicable diseases other than COVID-19 4. Discussion Mortality statistics are important measures during the COVID-19 pandemic [ 24 ] Comparable information about deaths and mortality rates as a starting point for informed health policy debate is essential. GBD follows the principles of ICD that a single underlying cause was assigned to each death [ 25 ].

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 9 of 16 Despite efforts to improve the quality and availability of mortality statistics, they are still, in a deplorable state as 4060 (13.9%) of mortalities are classified as ill-defined causes and 1485 (5.0%) as a null cause. This may be due to the urgent circumstances during the pandemic, as there was no access to standard care [ 26 ]. Similar problems are reported in disease reporting systems globally, e.g., weak infrastructure and rules [ 27 – 29 ]. From the total mortalities, the cause of death is assigned for no more than one-third and often considerably uncertain diagnosis [ 30 ]. Regarding NCDs mortality, NCDs encompass a vast group of diseases [ 31 ]. In the underlying NCDs causes of deaths in descending order were CVDs 10,103 (34.5%), cancer 1345 (4.6%), chronic respiratory diseases 1053 (3.9%), and diabetes 658 (2.2%). Inconsistent with the annual burden of global NCDs mortalities as CVDs diseases account for (17.7 million), followed by cancers (8.8 million), respiratory diseases (3.9 million), and diabetes (1.6 million) [ 32 ]. In this study, NCDs responsible for 15,340 (62.1%) of all mortalities, 13,159 (85.3%) of them are caused by the four disease clusters (CVDs, cancers, chronic respiratory diseases, and diabetes), while worldwide NCDs kill nearly 40 million people a year equivalent to 70% of all deaths, 32 million (80%) of all NCDs deaths are caused by the four disease clusters [ 32 ]. Therefore, the burden of NCDs is rising rapidly and has now become a major challenge to global development. This rapid increasing is due to multiple risk factors such as physical inactivity, sedentary lifestyle, economic development, increase in the use of tobacco, increase in the intake of processed foods high in sugar, fat, and salt, and change in cultural norms [ 33 ]. Comparing our results to the WHO country profile report in 2016, the overall mortalities from NCDs CVDs, and cancer are decreased from (73% to 62.1%), (37% to 34.6) and (10% to 4.6%) reciprocal, but CDs increased [ 32 ]. This can be attributed to the enormous progress in the socio-economic condition and changes in lifestyle in KSA [ 34 ]. In addition to The New Health Care Model as a part of the National Transformation Program, which launched in 2016 involves national screening programs focusing on diseases prevention and strengthening the primary health care system to screen risk or asymptomatic individuals, early diagnosis, and effective management [ 35 ]. In KSA, 2020, the top ten underlying causes of mortalities according to the ICD-10 in descending order were CVDs, infectious and parasitic diseases, injuries and poisoning, cancer, chronic respiratory disorders, (Road Transportation, and Traffic Accidents) RTTAs, Acute Respiratory Infections (ARIs), diabetes, Nervous System, and Sense organ disorders, maternal Conditions and neonatal causes, and Genitourinary diseases. That order changed from the top ten causes reported by the CDC, in 2018 ischemic heart disease, RTTA, stroke, chronic kidney disease, ARIs, Alzheimer’s disease, conflict and terror, cirrhosis, neonatal disorders, diabetes [ 36 ]. So currently, CVDs are considered the leading underlying cause of death in KSA [ 37 , 38 ] and both developing and developed countries [ 38 ]. The global agenda of NCDs have been expanded beyond the concept of four diseases to include mental health [ 39 ] in agreement with our finding that the mental, nervous, and sensory disorders became 678 (2.3%) Regarding NCDs mortalities per region; as a cause per province-specific MR were Najran, Al Jouf, Al-Qounfodah, and Makkah in order by (9.1, 8.9, 8.3, 8.2) and the lowest was in The Eastern region 2.6 per 10,000 of the province population. This can be explained by disparities in the provided health services e.g., the quality, accessibility, and preparedness during the pandemic, in addition to the heterogeneity among provinces; difference in gender composition, social, economic, legal, cultural, and political factors [ 40 ]. NCDs mortalities per age; ASMR counts 26.4/100,000 children less than 5 year, then decreased to be <12/100,000 at the age groups from (five–<45 year), then increases from (45–<50 year) to be 29.1 and doubled at the age (50–<55 year) to be 62.3/100,000 and so on Similar increasing trends. There were a significant difference in health status and NCDs mortalities between different age groups and sex can be attributed to the different levels of exposure and vulnerability to NCDs risk factors as reported by previous studies [ 41 , 42 ].

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 10 of 16 Regarding the pattern and trends of NCDs mortalities across months; (the number of mortality due to NCDs was 3019 at the end of January, then became 2146 at the end of April, to be 2894 by the 1 st of July 2020. This can be explained by the effective national response to manage this crisis through comprehensive national isolation policies, e.g., lockdown, active surveillance models, lifestyle changes, Telemedicine online services 24/7, outpatient support (937 call center), the ability to refill their medication, with secure cross-platform applications (App) e.g., Sehaty, Asseafny, and Tetamen Regarding CDs mortality in KSA, during the first half of 2020, the most common five CDs (other than COVID-19) namely, Streptococcal infection, Varicella, Mycoplasma Pneumonia, Tuberculosis, and Hepatitis. While between 2003–2016, they were hepatitis B, dengue fever, measles, chickenpox, and brucellosis [ 43 ]. Inconsistent with the estimated GBD study about 2020, the top causes of disability-adjusted life-years are projected to be lower respiratory infections, tuberculosis, diarrheal diseases, and Human Immune Deficiency virus (HIV) [ 44 ]. Despite technological developments in diagnostics, treatment, and vaccination programs, various infectious diseases have re-emerged in KSA [ 45 ] especially during the Summer season and religious congregations in Holy sites [ 46 ]. So CDs surveillance and reporting systems should be assessed in terms of quality, efficiency, and effectiveness [ 47 , 48 ] to be controlled as a public health priority to prevent the spread of contagious diseases [ 49 ]. CDs mortalities per age ;we reported that the top three CDs causing infant mortality (IM) were Septicemias, Varicella, and (Acute Respiratory Infection) ARI, while in the same duration in China they were ARI, diarrhea, and septicemias [ 50 ]. WHO reported that most neonatal mortalities are caused by preterm birth, intrapartum-related complications (birth asphyxia or lack of breathing at birth), infections, and birth defects. This may be attributed to conditions and diseases associated with lack of quality care at birth or skilled care and treatment immediately after birth and in the first days of life [ 51 ]. Among children under 5 years, CDs remain the leading cause of mortality. In this study, 236 (14.3 %) of mortalities were due to CDs, higher than in China (19%) [ 49 ], while 744 (45.2%) were due to NCDs. While WHO reported preterm birth complications, birth asphyxia/trauma, pneumonia, congenital anomalies, diarrhea, and malaria as leading causes [ 51 ]. This is because CDs can be avoided through prevention and treatment, education, and immunization campaigns, to achieve the Sustainable Development Goals (SDGs) to end preventable death of newborns and children under 5 years of age and to end CDs by 2030 [ 52 ]. As regards the pattern and trends of CDs including COVID-19; the mortalities across months reveals a major dramatic increase from 617 (10.8%) at the end of January and 717 (18.5%) at the end of April to 1620 (26.2%) at 1 July. The forced lockdown process has unexpected effects on the diffusion of infectious diseases, due to blocking of the vaccination campaign, [ 43 ] decreasing flow to the Emergency Department (ED), due to a common fear of being infected during ED in-stay, and a marked reduction in accesses to the hospitals [ 53 ]. As regards, COVID-19 mortality Estimating COVID-19 mortality during a pandemic is challenged because it includes only the diagnosed cases, that depend on the test rate that depends on the of the Saudi MOH Protocol (SMOHP), and other factors such as prevention measures of public health, health response, etc... [ 54 , 55 ]. COVID-19 mortality per sex; male to female ratio for COVID-19 deaths was 2.76, that higher than what was reported by The European Centre for Disease Prevention and Control (ECDC) across the EU was 2.1, and what was reported by The U.K.’s Office for National Statistics (ONS) as it was 2.0. This variation may be due to biological factors (during viral infections, women mount great antiviral, inflammatory, and humoral immune responses, while men showed higher levels of lymphocytes, white blood cells, and neutrophils [ 56 ], and gender differences (the combined effect of differences in legal, social, cultural, political, and economic norms [ 57 ], similar results reported in Peru, China, Pakistan, and Indonesia similar social, and cultural factors. In contrast, countries such as Canada and many European countries [ 58 ].

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 11 of 16 COVID-19 mortality per age group; ASMR/100 000 population of the same age group to be less than 2 in the population (<35 year), and progressively increased after the age group (55–<60 year) to be 17.7, then doubled at the age group (60–<65 year) and so on till reaching the highest 74.9 at the age group 80 year and more. So people >65 year have a multi-fold mortality risk than younger, consistent with previous reports [ 59 – 62 ] because aging deteriorates innate immunity thus increases the severity of infection, and risk of mortality. Elderly people are likely to be affected more due to the restrictive effect of COVID-19 related lifestyle changes, access to healthcare; which is expected to worsen the underlying medical conditions such as diabetes, hypertension, obesity, and dyslipidemia [ 61 , 62 ]. COVID-19 mortality per regions; There are variations in the COVID-19 MR among the elderly in various geographical regions of the world, and the percentage of deaths in the total closed cases is different across the provinces, being 1.60% in Makkah Province, 0.24% in Riyadh Province, 0.28% in Eastern Province, 0.57% in Al Madinah Province and 0.33% in Gazan Province [ 63 ] nearly similar to our statistics The infectious disease mortalities were 5005 (17.1%) due to the COVID-19 deaths While 2773 (9.4%) of mortalities were caused by injuries (unintentional and intentional), which stated by WHO to become more prevalent and were projected to show rates equal to mortality from infectious diseases by 2020. The SAMOH in collaboration with the WHO has emphasized improving the health situation by focusing on five key health issues; namely, (1) health security and disease prevention, (2) control of communicable diseases, (3) control of non-communicable diseases, (4) accidents and injuries, and (5) strengthening of health systems, on a priority basis [ 53 , 64 ] Regarding (Road Transportation, and Traffic Accidents) RTTAs mortalities WHO considered KSA to have the world’s highest mortalities from RTTAs, which was the main cause of death in adult males aged 16 to 36 year [ 65 ]. This evidence supports that the SA action plan focused mainly on the prevention of RTTIs rather than RTTAs, including seat belt laws, SAHER system, emergency medical services, and the role of the police in the documentation of RTAs [ 66 ]. While the international recommendations focused on developing an institutional framework, safer roads and vehicles, proper surveillance, and post-crash care [ 67 ]. As regards RTTA mortalities per region, KSA is a vast country of 2,149,690 km 2 [ 56 ]. The top regions regarding the occurrence of RTTAs mortalities were Riyadh, Makkah, Jeddah, and Asser was the highest 23.3%, 9.3%, 7.8%, and 7.4% and the lowest was in Al Jouf (0.4%). This can be explained by the highest population density (per km 2 ) as it is 101 in Jazan, and 38 in Makkah, and the lowest of 2.8 in Najran, and 3.6 in Al Jouf [ 65 ]. While in previous studies, the top regions were Riyadh, Jeddah, Makkah, AL-Madinah al Monawah, and Al-Qassem [ 68 ]. RTTAs mortalities trends across months; the RTTAs mortality reduced from 4.3% in February to 2.4% in April (Ramadan) then gradually increased with gradual reopen. Due to the lockdown, restricted travel, and recreation activities [ 69 ]. The months of RTTAs occurrence reported in few studies to be at the lowest rate 6.4% during February, while in Al Qassim, it was 5.8% in March [(16] inconsistent with our finding. Another study [ 70 ] reported that Ramadan (April) is the most common month for occurrence of RTTAs After the announcement of COVID-19 as a pandemic. This epidemiological trend has distressed most national healthcare services in developed countries with some extremely overwhelmed. Resulting in potentially, unexpected worse health outcomes due to the combination of frailty, aging, which affect NCDs, and increases the overall mortality [ 4 , 5 ]. Therefore, it is time to analyze the effects caused by the long lockdown period COVID-19 is a major global crisis [ 3 ], and its death certificate has a considerable role in the efforts to control the virus spread so that many countries have taken steps to ensure its accurate reporting [ 71 ]. It has resulted in lockdown in many parts worldwide Globally, till date 04 July 2020 (a total of 11,209,025 confirmed cases with 529,471 deaths and 6,356,170 completely recovered) [ 72 ].

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 12 of 16 Over months from the 30 th of April till the 1 st of July 2020, Although the strict preventive measurements and lockdown, but the pandemic morbidities and mortalities progressively increased thus altering the MR, so that the reported estimation of COVID-19 fatality rate in KSA had increased from 2% to 3.4% [ 73 ], inconsistent with most countries in which MR declined (except Italy, Mexico, and Germany), this happens due to disproportionation between the recovery rate and death rate [ 1 ]. The pattern of the outbreak differs considerably from the pattern experienced in Europe [ 43 ]. Similar patterns were seen in earlier outbreaks from the Coronavirus family, perhaps due to the similarities in the origin and the disease development. These patterns present another view of a neglected aspect of healthcare response, management of chronic disease, also an opportunity for health systems improvement, especially in emergency preparedness The sex and nationalities had a statistically significant relationship between the main underlying causes of death ( p < 0.05). This is because the differences in health-related behavior/lifestyle play an important role in explaining this significant relationship [ 74 ]. 4.1. Limitations There are many limitations; (1) There was no baseline comparison to other years; (2) Limitations of death reporting data; e.g., delayed reporting. Death reporting is affected by many considerations; The deaths that occur outside the health settings may be unattended, asymptomatic patients with mild clinical symptoms may be misdiagnosed or be ill-defined i.e., under-reporting of certain causes, and patients dying with infectious diseases are deemed to be dying from the disease 4.2. Strength This study is honest and transparent reporting about the mortality during the first wave of the COVID-19 pandemic. It is a baseline comparison comprehensive relevant national-based mortality data represents mortalities in KSA at the whole age groups, sex, provinces, causes, and nationalities, so the results can be generalized; meanwhile, the majority of studies were based on aggregate mortality data to serve limit group age, sex, and sex even the (GBDS) [ 75 ]. The COVID-19 mortalities were verified and confirmed through the Saudi National COVID-19 committee 5. Conclusions During the COVID-19 pandemic on the FIRST half of 2020 in KSA; NCDs mainly CVDs were the leading underlying causes of death; Male gender and old age > 55 year was a risk factor for worse outcomes and death in COVID-19 cases. The top six underlying causes of mortalities from CDs (other than COVID-19) were Streptococcal, varicella, Plaque, Mycobacterium Pneumonia, Hantavirus, and Cholera. Among children under 5 years, CDs remain the main underlying cause of mortality; The top regions regarding the occurrence of RTTAs mortalities were Riyadh, Makkah, Jeddah, and Asser; The lockdown was associated with a manifest reduction in the total number of deaths due to NCDs and RTTAs but increases the CDs mortalities. Sex and nationality were significantly associated with the main underlying causes of mortalities 6. Recommendations Many recommendations at different levels to strengthen the medical certification of death to be helpful guide for logistic planning; (1) at the level of documenting the cause of death in death certificate; by providing specialized physician, training programs on nosology as only one cause of death in death certificate except in complex causes a systematic classification is required, and improving the services to detect the causes of deaths. (2) At the level of coding; through providing well-trained persons in coding known as a nosologist because of the complexity of cause of death coding leads to specialized occupation/certification as a qualified nosologist. (3) At the registration level; to be done

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 13 of 16 only by trained qualified persons with continuous training and evaluation; (4) Increasing the number of mortality reporting health settings considering the population density and geographical accessibility. (5) Using a national specialized Soft Ware Program for online register with special requirement (obligate identity document (ID), and rejecting null causes or mismatched underlying and main causes); (6) At the future policy and services; using this up-to-date and reliable population-based statistics of mortality for needs assessments on national reprehensive base e.g., budget allocation and guided effective national programs based on the national burden of diseases e.g., Central Nervous System (CNS) programs. (7) Conducting National Researches to understand the patterns, trends, and main determinants to come up with evidence-based interventions and strengthen health system response 7. Ethical Considerations The collected data were managed privately and the identity was anonymous. The ethical approval was taken from the ethical committee of the research center at King Fahad Medical City IRB Log Number: 20-551 E Author Contributions: Conceptualization, A.M.A., S.A.A. (Shaker A. Alomary) and S.A.A (Saeed A. Alqahtani); Formal analysis, S.A.A. (Samar A. Amer); Investigation, A.M.A., S.A.A. (Shaker A. Alomary) and S.A.A. (Saeed A. Alqahtani); Methodology, S.A.A. (Samar A. Amer); Project administration, A.M.A. and S.A.A. (Shaker A. Alomary); Supervision, I.F.A.; Visualization, I.F.A.; Writing—original draft, S.A.A. (Samar A. Amer); Writing—review & editing, A.M.A., S.A.A (Shaker A. Alomary) and S.A.A. (Saeed A. Alqahtani). All authors have read and agreed to the published version of the manuscript Funding: No funding Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of king Fahad Medical City, Ministry of Health, KSA. Protocol log number 20-551 E, approved 25 August 2020 with IRP registration number at KACST, KSA H-01-R-012 of exempt type Data Availability Statement: The datasets used during the current study are available from the corresponding author or the principle investigator on reasonable request Acknowledgments: We thank all the Managers of the health care setting for their co-operation by providing the death registry. The authors gratefully acknowledge, and Manal Elimam for her support Our sincere gratitude goes to the Ethical Review Committee, King Fahad City for granting the ethical approval for this study Conflicts of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest References 1 WHO. WHO Director-General is Opening Remarks at the Media Briefing on COVID-19–11 March 2020. 2020. Published online March 11. Available online: https://www.who.int/director-general/speeches/detail/who-director-general-s-opening-remarksat-the-media-briefing-on-covid-19---11-march-2020 (accessed on 23 April 2020) 2 World Health Organization. WHO/Europe Past Pandemics. 2020. Available online: http://www.euro.who.int/en/healthtopics/communicable-diseases/influenza/pandemic-influenza/past-pandemics (accessed on 24 April 2020) 3 World Health Organization. Global Health Observatory Country Views. 2020. Available online: https://apps.who.int/gho/ data/node.country.country-SAU (accessed on 20 July 2020) 4 He, F.; Deng, Y.; Li, W. Coronavirus disease 2019: What we know? J. Med. Virol 2020 , 92 , 719–725. [ CrossRef ] 5 O’Donovan, M.R.; Sezgin, D.; Liew, A.; O’Caoimh, R. Burden of disease, disability-adjusted life years and frailty prevalence QJM Int. J. Med 2019 , 112 , 261–267. [ CrossRef ] 6 Azarpazhooh, M.R.; Morovatdar, N.; Avan, A.; Phan, T.G.; Divani, A.A.; Yassi, N.; Stranges, S.; Silver, B.; Biller, J.; Tokazebani Belasi, M.; et al. COVID-19 Pandemic and Burden of Non-Communicable Diseases: An Ecological Study on Data of 185 Countries J Stroke Cerebrovasc. Dis 2020 , 29 , 105089. [ CrossRef ] 7 Lozano, R.; Naghavi, M.; Foreman, K.; Lim, S.; Shibuya, K.; Aboyans, V.; Abraham, J.; Adair, T.; Aggarwal, R.; Ahn, Y.S.; et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010 Lancet 2012 , 380 , 2095–2128.

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Int. J. Environ. Res. Public Health 2021 , 18 , 12647 14 of 16 8 Lopez, A.D.; Mathers, C.D.; Ezzati, M.; Jamison, D.T.; Murray, C.J. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data Lancet 2006 , 367 , 1747–1757 9 World Health Organization. Global Health Observatory (GHO) Data. 2020. Available online: https://www.who.int/gho/ncd/ mortality_morbidity/en/ (accessed on 7 July 2020) 10 World Health Organization. Non-Communicable Diseases Fact Sheet. 2020. Available online: http://www.who.int/mediacentre/ factsheets/fs 355/en/ (accessed on 13 November 2013) 11 Alwan, A.; Maclean, D.R.; Riley, L.M.; d’Espaignet, E.T.; Mathers, C.D.; Stevens, G.A.; Bettcher, D. Monitoring and surveillance of chronic non-communicable diseases: Progress and capacity in high-burden countries Lancet 2010 , 376 , 1861–1868 12 Parkin, D.M.; Bray, F.; Ferlay, J.; Jemal, A. Cancer in Africa 2012 Cancer Epidemiol. Biomarkers Prev 2014 , 23 , 953–966 13 Mathers, C.D.; Loncar, D. Projections of global mortality and burden of disease from 2002 to 2030 PLoS Med 2006 , 3 , e 442 14 World Health Organization. Under Five Mortalities. 2010. Available online: http://www.who.int/whosis/en/index.html (accessed on 22 September 2020) 15 Kumar, A.; Mohanty, S.K Rich-Poor Gap in Infant and Under Five Mortalities in Urban India, 1992–05 ; International Institute for Population Sciences: Mumbai, India, 2009 16 Stevens, A.G.; Mathers, D.C.; Beard, R.J. Global mortality trends and patterns in older women Bull. World Health Organ 2013 , 91 , 630–639. [ CrossRef ] 17 National Centre for Health Statistics Health, United States, 1986 and Prevention Profile ; Public Health Service; US Department of Health and Human Services: Hyattsville, MA, USA, 1989; DHHS publication no. (PHS) 87-1232 18 Herzallah, H.K.; Antonisamy, B.R.; Shafee, M.H.; Al-Otaibi, S.T. Temporal trends in the incidence and demographics of cancers, communicable diseases, and non-communicable diseases in Saudi Arabia over the last decade Saudi Med. J 2019 , 40 , 277–286 [ CrossRef ] 19 Central Department of Statistics & Information. Highlights Demographic Survey 1428 H (2007). In Riyadh (KSA): National e-Government Portal ; 2007. Available online: www.cdsi.gov.sa (accessed on 29 August 2020) 20 World Health Organization International Statistical Classification of Diseases and Related Health Problems ; the 10 th Revision; World Health Organization: Geneve, Switzerland, 1992; Volume 1 21 Ahmad, O.; Boschi-Pinto, C.; Lopez, A.D.; Murray, C.J.; Lozano, R.; Inoue, M Age Standardization of Rates: A New WHO Standard ; World Health Organization: Geneva, Switzerland, 2001 22 Mathers, C.D.; Lopez, A.D.; Murray, C.J.L. The Burden of Disease and Mortality by Condition: Data, Methods and Results for 2001. In Global Burden of Disease and Risk Factors ; Lopez, A.D., Mathers, C.D., Ezzati, M., Jamison, D.T., Murray, C.J.L., Eds.; Oxford University Press: New York, NY, USA, 2006; pp. 45–240 23 Osypuk, T.L.; Joshi, P.; Geronimo, K.; Acevedo-Garcia, D. Do Social and Economic Policies Influence Health? A Review Curr Epidemiol. Rep 2014 , 1 , 149–164. [ CrossRef ] 24 The Global Burden of Disease (2004): 2004 Update ; World Health Organization: Geneva, Switzerland, 2008 25 Mortality and Causes of Death Collaborators. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: A systematic analysis for the Global Burden of Disease Study 2015 Lancet 2016 , 388 , 1459–1544. [ CrossRef ] 26 Janati, A.; Hosseiny, M.; Gouya, M.M.; Moradi, G.; Ghaderi, E. Communicable Disease Reporting Systems in the World: A Systematic Review Article Iran. J. Public Health 2015 , 44 , 1453–1465 27 Sahal, N.; Reintjes, R.; Mahgoub, A.E.; Aro, A.R. Staff views about the quality of the communicable diseases surveillance system in Khartoum state, Sudan, 2005–2007: A qualitative study East. Mediterr. Health J 2011 , 17 , 565–569 28 Shinde, R.R.; Kembhavi, R.S.; Kuwatada, J.S.; Khandednath, T.S. To develop a public private partnership model of disease notification as a part of integrated disease surveillance project (IDSP) for private medical practitioners in Mumbai City, India Glob. J. Med. Public Health 2012 , 1 , 1–11 29 Bino, S.; Cavaljuga, S.; Kunchev, A.; Lausevic, D.; Kaic, B.; Pistol, A.; Kon, P.; Karadjovski, Z.; Georghita, S.; Cicevalieva, S. Southeastern European Health Network (SEEHN) communicable diseases surveillance: A decade of bridging trust and collaboration Emerg. Health Threats J 2013 , 6 , 1–7 30 Cheng, Z.J.; Shan, J. 2019 Novel coronavirus: Where we are and what we know Infection 2020 , 48 , 155–163 31 Nethan, S.; Sinha, D.; Mehrotra, R. Non-Communicable Disease Risk Factors and their Trends in India Asian Pac. J. Cancer Prev APJCP 2017 , 18 , 2005–2010 32 World Health Organisation Global Status Report on Non-Communicable Diseases . 2014. Available online: http://www.who.int/ nmh/publications/ncd-status-report-2014/en/ (accessed on 11 January 2018) 33 Rawal, L.B.; Biswas, T.; Khandker, N.N.; Saha, S.R.; Bidat Chowdhury, M.M.; Khan, A.N.S.; Hasib Chowdhury, E.; Renzaho, A. Non-communicable disease (NCD) risk factors and diabetes among adults living in slum areas of Dhaka, Bangladesh PLoS ONE 2017 , 12 , e 0184967 34 World Health Organization Regional office for Eastern Mediterranean Cairo Egypt. Country Cooperation Strategy for Saudi Arabia 2006–2011. Available online: http://www.who.int/countryfocus/cooperation_strategy/ccs_sau_en.pdf.EM/ARD/014/ E/R (accessed on 13 September 2020) 35 Saudi Vision (2030). National Transformation Program: Strategic objectives. Available online: https://vision 2030.gov.sa/sites/ default/files/attachments/NTP%20 English%20 Public%20 Document_2810.pdf (accessed on 30 March 2019).

[Find the meaning and references behind the names: De Graaf, Zhang, Liu, Zou, Rizzi, Real, Soddu, Xiong, Xiang, Vogt, Nielsen, Dong, Hug, Raj, Kramer, David, Sheets, Daoud, Wang, Mokdad, Kebede, Ethiopia, Han, Wild, Piacenti, Hospital, Zaki, Jin, Bureau, Jian, Huang, Jun, Patnaik, Front, Tariku, Lauber, Perry, Snijder, Kang, Wei, Zhu, Graaf, Gong, Pomar, Miao, Abebe, Riva, Paladino, Casciaro, Colorado, Eltayeb, Ghosh, Tuffaha, Bellan, Zhou, Quick, Bai, Jama, Pan, Room, Favre, Russell, Chen, Musso, Case, Knowledge, Jaber, Hayden, Bank, Fauci, Washington, Yang, Qiu, Alemu, Ioannidis, Baud, Core, Young, Focus, Robinson, Bmc]

Int. J. Environ. Res. Public Health 2021 , 18 , 12647 15 of 16 36 GBD Compare World Bank 2018, Saudi Arabia ; Population Reference Bureau: Washington, DC, USA, 2018 37 Memish, Z.A.; El Bcheraoui, C.; Tuffaha, M.; Robinson, M.; Daoud, F.; Jaber, S. Obesity and Associated Factors Kingdom of Saudi Arabia Prev. Chronic Dis 2014 , 11 , 140236 38 Memish, Z.A.; Jaber, S.; Mokdad, A.H.; AlMazroa, M.A.; Murray, C.J.L.; Al Rabeeah, A.A. Burden of Disease, Injuries, and Risk Factors in the Kingdom of Saudi Arabia, 1990–2010 Prev. Chronic. Dis 2014 , 11 , 140176 39 Pan American Health Organization NCDs at a Glance: NCD Mortality and Risk Factor Prevalence in the Americas ; Paho: Washington, DC, USA, 2019 40 Liu, K.; Yang, J.; Zou, H. Cultural heterogeneity, social policy, and economic growth in China China Econ. Review 2020 , 62 , 101501 [ CrossRef ] 41 Abebe, S.M.; Andargie, G.; Shimeka, A.; Alemu, K.; Kebede, Y.; Wubeshet, M.; Tariku, A.; Gebeyehu, A.; Bayisa, M.; Yitayal, M.; et al. The prevalence of non-communicable diseases in Northwest Ethiopia: Survey of Dabat health and demographic surveillance system BMJ Open 2017 , 7 , e 015496. [ CrossRef ] 42 Liu, Y.; Liu, G.; Wu, H.; Jian, W.; Wild, S.H.; Gasevic, D. Sex differences in non-communicable disease prevalence in China: A cross-sectional analysis of the China health and retirement longitudinal study in 2011 BMJ Open 2017 , 7 , e 017450. [ CrossRef ] 43 Melingheri, M.; Paladino, M.E.; Piacenti, S.; Riva, M.A. Effects of COVID-19 lockdown on epidemic diseases of childhood J. Med Virol 2020 , 93 , 153–154. [ CrossRef ] 44 Deputy Director for Public Health Science and Surveillance, Center for Surveillance, Epidemiology, and Laboratory Services, Division of Scientific Education and Professional Development (2012). Available online: https://www.cdc.gov/ddphss/index. html (accessed on 22 May 2020) 45 David, M.M.; Fauci, A.S. Emerging Infectious Diseases: Threats to Human Health and Global Stability PLoS Pathog 2013 , 9 , e 1003467. [ CrossRef ] 46 Van Boheemen, S.; de Graaf, M.; Lauber, C.; Bestebroer, T.M.; Raj, V.S.; Zaki, A.M.; Osterhaus, A.D.; Haagmans, B.L.; Gorbalenya, A.E.; Snijder, E.J.; et al. Genomic characterization of a newly discovered coronavirus associated with acute respiratory distress syndrome in humans mBio 2012 , 3 , e 00473-12. [ CrossRef ] 47 Sahal, N.; Reintjes, R.; Eltayeb, E.M.; Aro, A.R. Assessment of core activities and supportive functions for the communicable diseases surveillance system in Khartoum state, Sudan, 2005–2007 East Mediterr. Health J 2010 , 16 , 1204–1210 48 Boehmer, T.K.; Patnaik, J.L.; Burnite, S.J.; Ghosh, T.S.; Gershman, K.; Vogt, R.L. Use of Hospital Discharge Data to Evaluate Notifiable Disease Reporting to Colorado’s Electronic Disease Reporting System Public Health Rep 2011 , 126 , 100–106 49 Kebede, S.; Gatabazi, J.B.; Rugimbanya, P.; Mukankwiro, T.; Perry, H.N.; Alemu, W.; Ndihokubwayo, B.J.; Kramer, H.M.; Mukabayire, O. Strengthening systems for communicable disease surveillance: Creating a laboratory network in Rwanda Health Res. Policy Syst 2011 , 9 , 1–8 50 Wang, K.; Xiang, L.; Kang, L.; Miao, L.; Li, Q.; Li, X.; Jun Zhu, J.; Wang, Y.; Huang, Y.; He, C. Communicable disease mortality trends and characteristics of infants in rural China, 1996–2015 BMC Public Health 2020 , 20 , 455. [ CrossRef ] 51 World Health Organization. Newborns: Improving Survival and Well-Being. 2020. Available online: https://www.who.int/ news-room/fact-sheets/detail/newborns-reducing-mortaliy (accessed on 19 September 2020) 52 Masquelier, B.; Hug, L.; Sharrow, D. Global, regional and national mortality trends in older children and young adolescents (5–14 years) from 1990 to 2016: An analysis of empirical data Lancet Glob. Health 2018 , 6 , e 1087–e 1099 53 Saudi Ministry of Health Guidelines on the Date of Death as it’s Continuously Updated on the National and International Basis ; Saudi Ministry of Health: Riyadh, Saudi Arabia, 2020 54 Baud, D.; Qi, X.; Nielsen-Saines, K.; Musso, D.; Pomar, L.; Favre, G. Real estimates of mortality following COVID-19 infection Lancet Infect. Dis 2020 , 20 , 773. Available online: https://www.thelancet.com/journals/laninf/article/PIIS 1473-3099(20)30195 -X/abstract (accessed on 27 March 2020) 55 Quick Interim Guide to COVID-19 Surveillance Case Definitions and Disposition. Available online: https//covid 19.cdc.gov.sa (accessed on 18 October 2020) 56 Jin, J.M.; Bai, P.; He, W.; Liu, S.; Wu, F.; Liu, X.F.; Han, D.M.; Liu, S.; Yang, J.K. Gender Differences in Patients with COVID-19: Focus on Severity and Mortality Front. Public Health 2020 , 8 , 152. [ CrossRef ] 57 Ng, J.; Bakrania, K.; Russell, R.; Falkous, R. Why Is the Disease Killing More Men than Women? COVID-19 Mortality Rates by Age and Gender. 2020. Available online: https//www.rgare.com/docs/defaultsource/knowledge-center-articles/covid-19 _mortality_age_gender.pdf?sfvrsn=5806 a 7 ea_4/ (accessed on 3 July 2020) 58 Bellan, M.; Gavelli, F.; Hayden, E.; Patrucco, F.; Soddu, D.; Pedrinelli, A.R.; Cittone, M.G.; Rizzi, E.; Casciaro, G.F.; Vassia, V.; et al. Pattern of emergency department referral during the COVID-19 outbreak in Italy Panminerva Med 2020 . [ CrossRef ] 59 Chen, N.; Zhou, M.; Dong, X.; Qu, J.; Gong, F.; Han, Y.; Qiu, Y.; Wang, J.; Liu, Y.; Wei, Y.; et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study Lancet 2020 , 395 , 507–513 [ CrossRef ] 60 Wang, D.; Hu, B.; Hu, C.; Zhu, F.; Liu, X.; Zhang, J.; Wang, B.; Xiang, H.; Cheng, Z.; Xiong, Y.; et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China JAMA 2020 , 323 , 1061–1069. [ CrossRef ] 61 Ioannidis, J.P.A.; Axfors, C.; Contopoulos-Ioannidis, D.G. Population-level COVID-19 mortality risk for non-elderly individuals overall and for non-elderly individuals without underlying diseases in pandemic epicentres Environ. Res 2020 , 188 , 109890.

[Find the meaning and references behind the names: Al Asiri, Code, Sharma, Ibrahim, Engl, Sci, Ann, Finelli, Iqbal, Meter, December, Zalat, Tripathy, Roy, Verma, Arafah, Naami, Full, Boretti, Mansuri, Iris, Need, Pak, Kaushal, Kar]

Int. J. Environ. Res. Public Health 2021 , 18 , 12647 16 of 16 62 Guilmoto, C.Z. COVID-19 Death Rates by Age and Sex and the Resulting Mortality Vulnerability of Countries and Regions in the World. 2020. Available online: https://www.medrxiv.org/content/10.1101/2020.05.17.20097410 v 1.full.pdf (accessed on 9 July 2020) 63 Boretti, A. COVID-19 fatality rate for Saudi Arabia, updated 3 June 2020 J. Glob. Antimicrob. Resist 2020 , 22 , 845–846. [ CrossRef ] 64 World Health Organization. Health Profile of Saudi Arabia. 2015. Available online: http://apps.who.int/iris/handle/10665/25 3771 (accessed on 28 December 2020) 65 World Health Organization Global Status Report on Road Safety 2013 ; World Health Organization: Geneva, Switzerland, 2013 66 Available online. Available online: https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html (accessed on 3 November 2020) 67 Mansuri, F.A.; Al-Zalabani, A.H.; Zalat, M.M.; Qabshawi, R.I. Road safety and road traffic accidents in Saudi Arabia Saudi Med. J 2015 , 36 , 418–424. [ CrossRef ] 68 Al-Naami, M.Y.; Arafah, M.A.; Al-Ibrahim, F.S. Trauma care systems in Saudi Arabia: An agenda for action Ann. Saudi Med 2010 , 30 , 50–58 69 Roy, D.; Tripathy, S.; Kar, S.K.; Sharma, N.; Verma, S.K.; Kaushal, V. Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian populatio during COVID-19 pandemic Asian J. Psychiatry 2020 , 51 , 102083 70 Khan, Z.U.; Al Asiri, K.M.; Iqbal, J. Injury patterns from road traffic accidents Pak. J. Med Sci 2010 , 26 , 394–397 71 Center of Disease Control (CDC). New ICD Code Introduced for COVID-19 Deaths. Available online: https://www.cdc.gov/ nchs/data/nvss/coronavirus/Alert-2-New-ICD-code-introduced-for-COVID-19-deaths.pdf (accessed on 9 July 2010) 72 World Meter. COVID-19 Coronavirus Pandemic. 2020. Available online: https://www.worldometers.info/coronavirus/ (accessed on 4 July 2020) 73 Lipsitch, M.; Swerdlow, D.L.; Finelli, L. Defining the Epidemiology of COVID-19—Studies Needed N. Engl. J. Med 2020 , 382 , 1194–1196 74 Our World in Data. 2020. Available online: covid.ourworldindata.org/data/owid-covid-data.csv (accessed on 3 June 2020) 75 Global Burden of Disease. Study Published. 2010. Available online: https://www.who.int/pmnch/media/news/2012/who_ burdenofdisease/en/ (accessed on 29 April 2020).

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