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Zhang H, Wang J, Liang Z, Wu Y. Non-linear effects of meteorological factors on COVID-19: An analysis of 440 counties in the americas. Heliyon 2024; 10:e31160. [PMID: 38778977 PMCID: PMC11109897 DOI: 10.1016/j.heliyon.2024.e31160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 05/09/2024] [Accepted: 05/10/2024] [Indexed: 05/25/2024] Open
Abstract
Background In the last three years, COVID-19 has caused significant harm to both human health and economic stability. Analyzing the causes and mechanisms of COVID-19 has significant theoretical and practical implications for its prevention and mitigation. The role of meteorological factors in the transmission of COVID-19 is crucial, yet their relationship remains a subject of intense debate. Methods To mitigate the issues arising from short time series, large study units, unrepresentative data and linear research methods in previous studies, this study used counties or districts with populations exceeding 100,000 or 500,000 as the study unit. The commencement of local outbreaks was determined by exceeding 100 cumulative confirmed cases. Pearson correlation analysis, generalized additive model (GAM) and distributed lag nonlinear model (DLNM) were used to analyze the relationship and lag effect between the daily new cases of COVID-19 and meteorological factors (temperature, relative humidity, solar radiation, surface pressure, precipitation, wind speed) across 440 counties or districts in seven countries of the Americas, spanning from January 1, 2020, to December 31, 2021. Results The linear correlations between daily new cases and meteorological indicators such as air temperature, relative humidity and solar radiation were not significant. However, the non-linear correlations were significant. The turning points in the relationship for temperature, relative humidity and solar radiation were 5 °C and 23 °C, 74 % and 750 kJ/m2, respectively. Conclusion The influence of meteorological factors on COVID-19 is non-linear. There are two thresholds in the relationship with temperature: 5 °C and 23 °C. Below 5 °C and above 23 °C, there is a positive correlation, while between 5 °C and 23 °C, the correlation is negative. Relative humidity and solar radiation show negative correlations, but there is a change in slope at about 74 % and 750 kJ/m2, respectively.
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Affiliation(s)
- Hao Zhang
- School of Geography, Nanjing Normal University, Nanjing, Jiangsu, 210023, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Jian Wang
- School of Geography, Jiangsu Second Normal University, Nanjing, Jiangsu, 211200, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu, 210023, China
| | - Zhong Liang
- School of Geography, Nanjing Normal University, Nanjing, Jiangsu, 210023, China
| | - Yuting Wu
- School of Geography, Nanjing Normal University, Nanjing, Jiangsu, 210023, China
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2
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Houweling L, Maitland-Van der Zee AH, Holtjer JCS, Bazdar S, Vermeulen RCH, Downward GS, Bloemsma LD. The effect of the urban exposome on COVID-19 health outcomes: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2024; 240:117351. [PMID: 37852458 DOI: 10.1016/j.envres.2023.117351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/06/2023] [Accepted: 10/07/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND The global severity of SARS-CoV-2 illness has been associated with various urban characteristics, including exposure to ambient air pollutants. This systematic review and meta-analysis aims to synthesize findings from ecological and non-ecological studies to investigate the impact of multiple urban-related features on a variety of COVID-19 health outcomes. METHODS On December 5, 2022, PubMed was searched to identify all types of observational studies that examined one or more urban exposome characteristics in relation to various COVID-19 health outcomes such as infection severity, the need for hospitalization, ICU admission, COVID pneumonia, and mortality. RESULTS A total of 38 non-ecological and 241 ecological studies were included in this review. Non-ecological studies highlighted the significant effects of population density, urbanization, and exposure to ambient air pollutants, particularly PM2.5. The meta-analyses revealed that a 1 μg/m3 increase in PM2.5 was associated with a higher likelihood of COVID-19 hospitalization (pooled OR 1.08 (95% CI:1.02-1.14)) and death (pooled OR 1.06 (95% CI:1.03-1.09)). Ecological studies, in addition to confirming the findings of non-ecological studies, also indicated that higher exposure to nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and carbon monoxide (CO), as well as lower ambient temperature, humidity, ultraviolet (UV) radiation, and less green and blue space exposure, were associated with increased COVID-19 morbidity and mortality. CONCLUSION This systematic review has identified several key vulnerability features related to urban areas in the context of the recent COVID-19 pandemic. The findings underscore the importance of improving policies related to urban exposures and implementing measures to protect individuals from these harmful environmental stressors.
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Affiliation(s)
- Laura Houweling
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Anke-Hilse Maitland-Van der Zee
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Judith C S Holtjer
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands
| | - Somayeh Bazdar
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
| | - Roel C H Vermeulen
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - George S Downward
- Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Lizan D Bloemsma
- Dept. of Pulmonary Medicine, Amsterdam UMC, Amsterdam, the Netherlands; Amsterdam Institute for Infection and Immunity, Amsterdam, the Netherlands; Amsterdam Public Health, Amsterdam, the Netherlands
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Zhou C, Fang J, Mao M. A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1028. [PMID: 37509975 PMCID: PMC10378078 DOI: 10.3390/e25071028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/22/2023] [Accepted: 07/04/2023] [Indexed: 07/30/2023]
Abstract
Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple groups were equal during the epidemic period. In light of large-scale simulation studies, the proposed test method can accurately identify the differences between different groups and display satisfactory performance. We apply the proposed method to the real dataset of the COVID-19 epidemic in mainland China (excluding Hubei), Hubei Province (excluding Wuhan), and Wuhan from 31 January 2020 to 30 March 2020. By comparing the differences in the disease severity for differential cities, we show that the severity of the early disease of COVID-19 may be related to the effectiveness of interventions and the improvement in medical resources.
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Affiliation(s)
- Chuanbo Zhou
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Jiaohong Fang
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
| | - Mingzhi Mao
- School of Mathematics and Physics, China University of Geosciences, Wuhan 430074, China
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Donzelli G, Biggeri A, Tobias A, Nottmeyer LN, Sera F. Role of meteorological factors on SARS-CoV-2 infection incidence in Italy and Spain before the vaccination campaign. A multi-city time series study. ENVIRONMENTAL RESEARCH 2022; 211:113134. [PMID: 35307374 PMCID: PMC8928740 DOI: 10.1016/j.envres.2022.113134] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/15/2022] [Accepted: 03/15/2022] [Indexed: 05/07/2023]
Abstract
Numerous studies have been conducted worldwide to investigate if an association exists between meteorological factors and the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection incidence. Although research studies provide conflicting results, which can be partially explained by different methods used, some clear trends emerge on the role of weather conditions and SARS-CoV-2 infection, especially for temperature and humidity. This study sheds more light on the relationship between meteorological factors and SARS-CoV-2 infection incidence in 23 Italian and 52 Spanish cities. For the purposes of this study, daily air temperature, absolute and relative humidity, wind speed, ultraviolet radiation, and rainfall are considered exposure variables. We conducted a two-stage meta-regression. In the first stage, we estimated the exposure-response association through time series regression analysis at the municipal level. In the second stage, we pooled the association parameters using a meta-analytic model. The study demonstrates an association between meteorological factors and SARS-CoV-2 infection incidence. Specifically, low levels of ambient temperatures and absolute humidity were associated with an increased relative risk. On the other hand, low and high levels of relative humidity and ultraviolet radiation were associated with a decreased relative risk. Concerning wind speed and rainfall, higher values contributed to the reduction of the risk of infection. Overall, our results contribute to a better understanding of how the meteorological factors influence the spread of the SARS-CoV-2 and should be considered in a wider context of existing robust literature that highlight the importance of measures such as social distancing, improved hygiene, face masks and vaccination campaign.
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Affiliation(s)
- Gabriele Donzelli
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy.
| | - Annibale Biggeri
- Department of Cardio, Thoracic, Vascular Sciences and Public Health, University of Padua, Padua, Italy.
| | - Aurelio Tobias
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Spain; School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan.
| | - Luise N Nottmeyer
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
| | - Francesco Sera
- Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence, Florence, Italy.
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Tateo F, Fiorino S, Peruzzo L, Zippi M, De Biase D, Lari F, Melucci D. Effects of environmental parameters and their interactions on the spreading of SARS-CoV-2 in North Italy under different social restrictions. A new approach based on multivariate analysis. ENVIRONMENTAL RESEARCH 2022; 210:112921. [PMID: 35150709 PMCID: PMC8828377 DOI: 10.1016/j.envres.2022.112921] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/13/2022] [Accepted: 02/06/2022] [Indexed: 02/07/2023]
Abstract
In 2020 North Italy suffered the SARS-CoV-2-related pandemic with a high number of deaths and hospitalization. The effect of atmospheric parameters on the amount of hospital admissions (temperature, solar radiation, particulate matter, relative humidity and wind speed) is studied through about 8 months (May-December). Two periods are considered depending on different conditions: a) low incidence of COVID-19 and very few regulations concerning personal mobility and protection ("free/summer period"); b) increasing incidence of disease, social restrictions and use of personal protections ("confined/autumn period"). The "hospitalized people in medical area wards/100000 residents" was used as a reliable measure of COVID-19 spreading and load on the sanitary system. We developed a chemometric approach (multiple linear regression analysis) using the daily incidence of hospitalizations as a function of the single independent variables and of their products (interactions). Eight administrative domains were considered (altogether 26 million inhabitants) to account for relatively homogeneous territorial and social conditions. The obtained models very significantly match the daily variation of hospitalizations, during the two periods. Under the confined/autumn period, the effect of non-pharmacologic measures (social distances, personal protection, etc.) possibly attenuates the virus diffusion despite environmental factors. On the contrary, in the free/summer conditions the effects of atmospheric parameters are very significant through all the areas. Particulate matter matches the growth of hospitalizations in areas with low chronic particulate pollution. Fewer hospitalizations strongly correspond to higher temperature and solar radiation. Relative humidity plays the same role, but with a lesser extent. The interaction between solar radiation and high temperature is also highly significant and represents surprising evidence. The solar radiation alone and combined with high temperature exert an anti-SARS-CoV-2 effect, via both the direct inactivation of virions and the stimulation of vitamin D synthesis, improving immune system function.
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Affiliation(s)
- Fabio Tateo
- Institute of Geosciences and Earth Resources (IGG), National Research Council of Italy (CNR), Via G. Gradenigo, 6, 35131, Padova, Italy
| | - Sirio Fiorino
- Internal Medicine Unit, Budrio Hospital, Azienda USL, Via Benni, 44, 40054, Bologna, Italy
| | - Luca Peruzzo
- Institute of Geosciences and Earth Resources (IGG), National Research Council of Italy (CNR), Via G. Gradenigo, 6, 35131, Padova, Italy.
| | - Maddalena Zippi
- Unit of Gastroenterology and Digestive Endoscopy, Sandro Pertini Hospital, Via dei Monti Tiburtini 385, 00157, Rome, Italy
| | - Dario De Biase
- Department of Pharmacy and Biotechnology, University of Bologna, Via Belmeloro 6, 40126, Bologna, Italy
| | - Federico Lari
- Internal Medicine Unit, Budrio Hospital, Azienda USL, Via Benni, 44, 40054, Bologna, Italy
| | - Dora Melucci
- Department of Chemistry Ciamician, University of Bologna, Via Selmi, 2, 40126, Bologna, Italy
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County-Level Assessment of Vulnerability to COVID-19 in Alabama. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2022. [DOI: 10.3390/ijgi11050320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The COVID-19 pandemic has posed an unprecedented challenge to public health across the world and has further exposed health disparities and the vulnerability of marginal groups. Since the pandemic has exhibited marked regional differences, it is necessary to better understand the levels of vulnerability to the disease at local levels and provide policymakers with additional tools that will allow them to develop finely targeted policies. In this study, we develop for the State of Alabama (USA) a composite vulnerability index at county level that can be used as a tool that will help in the management of the pandemic. Twenty-four indicators were assigned to the following three categories: exposure, sensitivity, and adaptive capacity. The resulting subindices were aggregated into a composite index that depicts the vulnerability to COVID-19. A multivariate analysis was used to assign factor loadings and weights to indicators, and the results were mapped using Geographic Information Systems. The vulnerability index captured health disparities very well. Many of the most vulnerable counties were found in the Alabama Black Belt region. A deconstruction of the overall index and subindices allowed the development of individual county profiles and the detection of local strengths and weaknesses. We expect the model developed in this study to be an efficient planning tool for decision-makers.
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Wang J, Zhang L, Lei R, Li P, Li S. Effects and Interaction of Meteorological Parameters on Influenza Incidence During 2010-2019 in Lanzhou, China. Front Public Health 2022; 10:833710. [PMID: 35273941 PMCID: PMC8902077 DOI: 10.3389/fpubh.2022.833710] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/10/2022] [Indexed: 11/13/2022] Open
Abstract
Background Influenza is a seasonal infectious disease, and meteorological parameters critically influence the incidence of influenza. However, the meteorological parameters linked to influenza occurrence in semi-arid areas are not studied in detail. This study aimed to clarify the impact of meteorological parameters on influenza incidence during 2010-2019 in Lanzhou. The results are expected to facilitate the optimization of influenza-related public health policies by the local healthcare departments. Methods Descriptive data related to influenza incidence and meteorology during 2010-2019 in Lanzhou were analyzed. The exposure-response relationship between the risk of influenza occurrence and meteorological parameters was explored according to the distributed lag no-linear model (DLNM) with Poisson distribution. The response surface model and stratified model were used to estimate the interactive effect between relative humidity (RH) and other meteorological parameters on influenza incidence. Results A total of 6701 cases of influenza were reported during 2010-2019. DLNM results showed that the risk of influenza would gradually increase as the weekly mean average ambient temperature (AT), RH, and absolute humidity (AH) decrease at lag 3 weeks when they were lower than 12.16°C, 51.38%, and 5.24 g/m3, respectively. The low Tem (at 5th percentile, P5) had the greatest effect on influenza incidence; the greatest estimated relative risk (RR) was 4.54 (95%CI: 3.19-6.46) at cumulative lag 2 weeks. The largest estimates of RRs for low RH (P5) and AH (P5) were 4.81 (95%CI: 3.82-6.05) and 4.17 (95%CI: 3.30-5.28) at cumulative lag 3 weeks, respectively. An increase in AT by 1°C led to an estimates of percent change (95%CI) of 3.12% (-4.75% to -1.46%) decrease in the weekly influenza case counts in a low RH environment. In addition, RH showed significant interaction with AT and AP on influenza incidence but not with wind speed. Conclusion This study indicated that low AT, low humidity (RH and AH), and high air pressure (AP) increased the risk of influenza. Moreover, the interactive effect of low RH with low AT and high AP can aggravate the incidence of influenza.
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Affiliation(s)
- Jinyu Wang
- School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Ling Zhang
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Ruoyi Lei
- Institute of Occupational Health and Environmental Health, School of Public Health, Lanzhou University, Lanzhou, China
| | - Pu Li
- The Second People's Hospital of Baiyin, Baiyin, China
| | - Sheng Li
- The First People's Hospital of Lanzhou, Lanzhou, China
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Abdel-Aal MAM, Eltoukhy AEE, Nabhan MA, AlDurgam MM. Impact of climate indicators on the COVID-19 pandemic in Saudi Arabia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:20449-20462. [PMID: 34735701 PMCID: PMC8566192 DOI: 10.1007/s11356-021-17305-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 10/27/2021] [Indexed: 04/12/2023]
Abstract
The novel coronavirus (COVID-19) outbreak has left a major impact on daily lifestyle and human activities. Many recent studies confirmed that the COVID-19 pandemic has human-to-human transmissibility. Additional studies claimed that other factors affect the viability, transmissibility, and propagation range of COVID-19. The effect of weather factors on the spread of COVID-19 has gained much attention among researchers. The current study investigates the relationship between climate indicators and daily detected COVID-19 cases in Saudi Arabia, focusing on the top five cities with confirmed cases. The examined climate indicators were temperature (°F), dew point (°F), humidity (%), wind speed (mph), and pressure (Hg). Using data from Spring 2020 and 2021, we conducted spatio-temporal correlation, regression, and time series analyses. The results provide preliminary evidence that the COVID-19 pandemic spread in most of the considered cities is significantly correlated with temperature (positive correlation) and pressure (negative correlation). The discrepancies in the results from different cites addressed in this study suggest that non-meteorological factors need to be explored in conjunction with weather attributes in a sufficiently long-term analysis to provide meaningful policy measures for the future.
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Affiliation(s)
- Mohammad A. M. Abdel-Aal
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, 5063, Dhahran, 31261 Saudi Arabia
- IRC of Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261 Saudi Arabia
| | - Abdelrahman E. E. Eltoukhy
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR China
| | - Mohammad A. Nabhan
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, 5063, Dhahran, 31261 Saudi Arabia
| | - Mohammad M. AlDurgam
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, 5063, Dhahran, 31261 Saudi Arabia
- IRC of Smart Mobility and Logistics, King Fahd University of Petroleum and Minerals, Dhahran, 31261 Saudi Arabia
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Iqbal A, Haq W, Mahmood T, Raza SH. Effect of meteorological factors on the COVID-19 cases: a case study related to three major cities of the Kingdom of Saudi Arabia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:21811-21825. [PMID: 34767172 PMCID: PMC8586838 DOI: 10.1007/s11356-021-17268-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/25/2021] [Indexed: 06/13/2023]
Abstract
The COVID-19 pandemic affected the world through its ability to cause widespread infection. The Middle East including the Kingdom of Saudi Arabia (KSA) has also been hit by the COVID-19 pandemic like the rest of the world. This study aims to examine the relationships between meteorological factors and COVID-19 case counts in three cities of the KSA. The distribution of the COVID-19 case counts was observed for all three cities followed by cross-correlation analysis which was carried out to estimate the lag effects of meteorological factors on COVID-19 case counts. Moreover, the Poisson model and negative binomial (NB) model with their zero-inflated versions (i.e., ZIP and ZINB) were fitted to estimate city-specific impacts of weather variables on confirmed case counts, and the best model is evaluated by comparative analysis for each city. We found significant associations between meteorological factors and COVID-19 case counts in three cities of KSA. We also perceived that the ZINB model was the best fitted for COVID-19 case counts. In this case study, temperature, humidity, and wind speed were the factors that affected COVID-19 case counts. The results can be used to make policies to overcome this pandemic situation in the future such as deploying more resources through testing and tracking in such areas where we observe significantly higher wind speed or higher humidity. Moreover, the selected models can be used for predicting the probability of COVID-19 incidence across various regions.
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Affiliation(s)
- Anam Iqbal
- Department of Statistics, Government Graduate College for Women, Sargodha, Punjab, Pakistan
| | - Wajiha Haq
- Department of Economics, School of Social Sciences and Humanities, National University of Sciences and Technology, Islamabad, H-12, Pakistan.
| | - Tahir Mahmood
- Industrial and Systems Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
- Interdisciplinary Research Centre for Smart Mobility & Logistics, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
| | - Syed Hassan Raza
- School of Economics, Quaid-i-Azam University, Islamabad, Pakistan
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