| Literature DB >> 35352307 |
Sekmoudi Imane1, Bouakline Oumaima2, Khomsi Kenza3,4, Idrissi Laila1, El Merabet Youssef5, Souhaili Zineb4, El Jarmouni Mohamed6.
Abstract
PURPOSE OF REVIEW: The aim of this review is to summarize and provide clear insights into studies that evaluate the interaction between air pollution, climate, and health in North Africa. RECENTEntities:
Keywords: Air pollution; Climate; Climate extremes; Health; Mental disorders; North Africa; Vector-borne disease
Mesh:
Substances:
Year: 2022 PMID: 35352307 PMCID: PMC8964241 DOI: 10.1007/s40572-022-00350-y
Source DB: PubMed Journal: Curr Environ Health Rep ISSN: 2196-5412
Fig. 1The search strategy
Fig. 2The study area
The characteristics of the epidemiological studies included in the present review regarding air pollution and public health
| Authors, year | Study area | Calculated health effects | DATA | Population age | Included periods | Factors taken into account | Methods | Main results |
|---|---|---|---|---|---|---|---|---|
| Ghennam, Attou and Abdoun, 2021 | Algeria | Asthma and bronchitis hospital admissions | The index of atmospheric purity (IAP), the index of human impact (IHI), environmental parameters, and the respiratory illness data from Algerian hospital | Not specified | Between 2006 and 2016 | 976 cases taken into account including 771 with asthma and 205 with bronchitis | Redundancy analysis is used to quantify the relationship and the influence of air pollution and environmental parameters on respiratory diseases | Atmospheric pollutions contribute significantly in asthma and bronchitis with higher frequency related to hospital admission for asthma |
| Boussetta et al., 2020 | Tunisia | The impact of polluted area (PA) on the performance of athletes, cardiovascular, muscle damage, and oxidative stress | Data of cardiovascular parameters, damage markers, and oxidative stress markers | Mean age 22.45 | Randomized experimental protocol | Similarity of weather and climate | Comparison of measured parameters in two areas (i.e., polluted (PA) and non-polluted (NPA)) and the quantification of the impact of red orange juice supplementation (ROJS) | The impact of polluted areas on the athlete’s health could be mitigated using red orange juice supplementation |
| Marchetti et al., 2019 | Greater Cairo (Egypt) | Effects in human lung cells that are attributed to | The fine | Not specified | From December 2016 to November 2017 | Seasonal variability | Correlations between Chemical Parameters and Biological Effects | |
| Mohammed, Ibrahim and Saleh, 2019 | Egypt: Shoubra El-Khaima and Ain Sokhna sectors | Not specified | From December 2015 to November 2016 | Shoubra El-Khaima and Ain Sokhna population | Air Q 2.2.3 Software | Results showed important differences in the ( | ||
| Wheida et al., 2018 | Greater Cairo (Egypt) | Mortality attributable to long-term exposure to | All ages | From 2000 to 2004 and from 2010 to 2015 | Age and Greater Cairo population | AirQ + Software. The used concentration–response functions (CRF) are log-linear, linear, and log–log | ||
| Croitoru and Sarraf, 2017 | Morocco | Mortality and morbidity related to human exposure to ambient | All ages | The period 2012–2015 | Moroccan population, and age | Applying Integrated Exposure–Response Functions (IER) to | Adults over 55 years old are more vulnerable for premature deaths owing to air pollution due to ischemic heart disease and stroke and children under 5 years old are the ones most at risk of premature fatalities caused by air pollution due to acute lower respiratory infections | |
| Malley et al., 2017 | The globe including North Africa | National population-weighted, annual average ambient | Not specified | 2010 | Data for 183 countries | Concentration response functions (CRF) from previous studies that are conducted in the USA and Europe | Regardless of the limitations and uncertainties in the estimations, results demonstrate that maternal | |
| Boussetta et al., 2017 | Tunisia | The effect of air pollution on the performance in anaerobic tests and cardiovascular and hematological parameters | Data of cardiovascular parameters, blood measurement, and anaerobic performances | Mean age: 21.8 [range: 20–24] | Test sessions in the morning (07:00–09:00 h) and in the evening (17:00–19:00 h) | Similarity of weather and climate | Comparison of measured parameters in two areas (i.e., polluted (PA) and non-polluted (NPA)) | Polluted area influences health and athletic training performances and the impact is more aggravated at the evening |
| Benaissa et al., 2016 | Bejaia City (Algeria) | All-cause mortality and respiratory and cardiovascular hospitalizations related to short-term exposure to ambient | All ages | From 04/08/2015 to 07/14/2015 | Population of Bejaia (Algeria) | Traditional health impact assessment methods are used to analyze the impact of short-term exposure to | In 2014, the excess in |
The characteristics of the epidemiological studies included in the present review regarding climate and public health
| Authors, year | Study area | Calculated health effects | Data | Population, age | Included period | Factors taken into account | Methods | Main results |
|---|---|---|---|---|---|---|---|---|
| Outammassine et al., 2021 | Morocco | Modeling and mapping of the habitat suitability and the potential distribution of arboviruses vectors | Dataset records for | Not applicable | From 1916 to 2017 | Altitude, temperature, and precipitation | Maximum entropy (Maxent) modeling under current climatic conditions | Areas with maximum risk and high potential distribution were mainly located in the northwestern and central parts of Morocco |
| Gijón‐Robles et al., 2021 | Morocco Anthroponotic cutaneous leishmaniasis (ACL) endemic area (El Borouj) and non-endemic area (Sidi Hajjaj) | Comparison of the densities and genetic characteristics of | Data from captured Sand flies | Not applicable | June 20 to July 10 and from September 20 to October 10, 2015 | Temperature, precipitation | Sand flies capture using CDC light traps inside households and sticky papers outside dwellings, Sand fly DNA extraction, Mitochondrial lineage determination by mt DNA Cyt b PCR–RFLP Polymerase | |
| Ryan et al., 2021 | Global including north Africa | First systematic assessment of where future temperatures are expected to become suitable for Zika virus (ZIKV) transmission | Thermal responses for mosquito and virus traits that drive transmission | Population at risk based on human population density data from 2015 | 2050 | Temperature, human population density | Temperature-dependent transmission model for Zika virus (ZIKV). | Over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050 |
| Bettaieb et al., 2020 | Tunisia | Impact of heat on daily all-cause mortality | Daily time series of mortality; daily mean, minimum, and maximum temperature (in °C); relative humidity (in %); wind speed (in m/s) and direction (in rose 368; sea level pressure (in hPa) NO2 (in µg/m3) | Population of Tunis | Summer season (May–October) of a 3-year period (2005 to 2007) | Weather, air pollution | The Generalized Additive Model (GAM) using cubic regression splines and Akaike’s Information Criterion (AIC) A segmented linear regression and the Muggeo’s approach to estimate the breakpoint. Poisson Generalized Estimating Equations (GEE) | Daily mortality increased significantly by 2% for an 18 °C increase in daily maximum temperature above the breakpoint |
| Essayagh et al., 2020 | Meknes, Morocco | Cases of typhoid fever | Socio-demographic information, clinical, and paraclinical data; season; notion of contagiousness; food consumed; water supply; waste water disposal; notion of bathing and evolution of the case | Confirmed cases of typhoid fever ¨de at health centers or hospitals in Meknes | 2013–2016 | Seaonal study, temperature | Case series study using an epidemiological surveillance database | The number of cases of fever typhoid was highest in the dry season. Climatic conditions could facilitate the invasion of certain pathogens. The analysis during the different periods showed notable changes during the different seasons of the year with a high average incidence in the dry season (5 cases per 100,000 inhabitants in summer and 2.8 cases per 100,000 inhabitants in spring) |
| Elsobky et al., 2020 | Menoufia, Egypt | Climate impact on HPAI-H5N1disease variability | Domestic poultry HPAI-H5N1 outbreak | Not applicable | January 2006 to December 2016 | Temperature, relative humidity | General Linear Model (GLM) Generalized estimating equations (GEEs) | Effect of climate variability differs according to the timing of the outbreak occurrence |
| Maryam Hakkour et al., 2020 | Nine provinces located in the extreme and central north of Morocco (Aounate, Taza, Chefchaouen, Al Hoceima, Larache, T ´etouane,Tanger-Assilah, M’diq-Fnideq, and Fahs-Anjra Provinces) | Leishmaniasis cases | Human case. Environmental variables | A total of 6128 cases in the 9 provinces | 1997–2018 | Humidity, temperature | Linear regression model | Humidity was significant for both CL and VL ( |
| Hajar El Omari et al., 2020 | Meknes prefecture, Morocco | The abundance of sandflies indicator of the risk of leishmaniasis | Meteorological data. climate factors | Phle-botomian population | From March 2016 until April 2017 | Temperature, humidity, precipitation | Principal component analysis (PCA) | The existence of a positive correlation between the temperature and the abundance of sandflies ( |
| Aly Zein Elabdeen Kassem et al., 2020 | Forty-three countries including Morocco and Tunisia | COVID-19 cases per million | Total number of confirmed cases | COVID-19 cases | January–July 2020 | Temperature | Non-linear least squares method | Inverse relationship between COVID-19 cases per million and the temperature in just two observations out of twelve other factors than temperature is the most influential on the transmission of COVID-19 |
| S.A. MEO et al., 2020 | 20 countries of the globe including Algeria | Mean daily case incidence, cumulative cases, and cumulative deaths of COVID-19 | Metrological data, daily new cases, and deaths of COVID-19 | population of the 20 countries including Algeria | Dec 29, 2019 to May 12, 2020 | Temperature | Simple linear regression analysis | The COVID-19 cases and deaths per million population were significantly low in countries with high temperature and low humidity (warmest countries), compared to those countries with low temperatures and high humidity (coldest countries) |
| humidity | ||||||||
| Saverio Bellizzi et al., 2020 | Eastern Mediterranean Region including Morocco, Tunisia, Egypt, and libya | The health consequence vulnerability index, mortality, morbidity | Publicly available articles in PubMed, data displayed on the WHO Regional Health Observatory, EMR specific program documents, and on WHO Country Office reports. Documentation on access to water and sanitation in the EMR countries. UNHCR figures on internally displaced Persons (IDPs) | Under-5-all population of Eastern Mediterranean Region | From 1990 through 2019 | Health status of the population before the disaster; infrastructure like water supply and sanitation systems; food insecurity; absence of warning systems; population displacement; and other concurrent situations like economic crisis, political instability, and armed conflict | A review of scientific literature and WHO EMR documentation. Calculation of index score for each country based on the vulnerability factor scores | The WHO Eastern Mediterranean Region remains a highly vulnerable area of the world in terms of health consequences due to drought. The effects of drought have potentially greater impact on individual with underlying chronic medical conditions such as respiratory diseases as well as on persons with disabilities, who may not be able to access emergency response services due to the difficulties in mobility, hearing, seeing, and understanding Fifteen million people remain without even basic water services, live in Iraq, Islamic Republic of Iran, and Morocco. Morocco and Tunisia are the two countries among the 9 out of 22 EMR countries with safe drinking water management. Seventeen million people remain without basic sanitation services, living in Egypt, Iraq, and Morocco. Access to water and soap for hand washing varies widely, from 10% in Somalia to about 90% in Tunisia, Egypt, and Iraq |
| Caini et al., 2019 | A total of 31 countries including Morocco from north Africa | Epidemiological characteristics, pattern of circulation, and geographical distribution of influenza B viruses and its B/Victoria and B/Yamagata lineages | The GIBS database of epidemiological and virological influenza surveillance data from thirty-one countries around the world | All population | 2000–2018 | Age (exact age or age groups) | A statistical approach. The non-parametric Kruskal–Wallis test. EPIPOI software (Alonso WJ, McCormick BJ. EPIPOI: a user-friendly analytical tool for the extraction and visualization of temporal parameters from epidemiological time series. BMC Public Health. 2012; 12(1):982. 27.) | B/Yamagata was more frequent in countries that have temperate climate |
| Bauer et al., 2019 | Thirty-two countries including Tunisia | Association between solar insolation and a history of suicide attempt in patients with bipolar I disorder | A total of 3365 patients from 310 onset locations, 50 sites in 32 countries | A total of 1047 patients that had a history ofsuicide attempt | 2010 to 2016 | Sex, a history of alcohol or substance abuse, belonging to younger birth cohort, living in a country with a state-sponsored religion | Diagnosis of bipolar disorder according to DSM-IV criteria from a psychiatrist, direct questioning, reviewing records, or both | A significant inverse association between a history of suicide attempt and the ratio of mean winter solar insolation/mean summer solar insolation. Living in locations with large changes in solar insolation between winter and summer may be associated with increased suicide attempts in patients with bipolar disorder |
| Ahmed H. Salaheldin et al., 2018 | Four governorates from Egypt (Alexandria, Cairo, Minya, and Luxor) | Total number of A/H5N1 outbreaks per month | Total number of A/H5N1 outbreaks per month. Six viruses from the repository of the Friedrich-Loeffler-Institut | - | Ten seasons from 2006 to 2015. From the 1st of October to 31st of March | Climatic factors (temperature, relative humidity, and wind speed), biological fitness in vitro, and pathogenicity in domestic Pekin and Muscovy ducks | Negative binomial regression models | Ambient temperature in winter months influenced the spread of avian influenza virus A/H5N1 |
| Ait Kbaich et al., 2017 | Ouarzazate and Zagoura provinces in Morocco | Identification of Leishmania species causing CL in the two provinces | Eighty-one samples collected from patients | Eighty-one suspected CL patients. Four months to 56 years | 2015 & 2016 | Age, sex, travel history | Tissue sampling collected by dermal scraping from the 81 patients. DNA extraction and PCR–RFLP analysis. ITS1 PCR–RFLP of Leishmania species | Epidemiological pattern of CL in the studied areas appears to have changed, from a predominantly zoonotic CL caused by L. major to a polymorphic CL that can be due to either of the 3 leishmania species |
| Alkishe et al., 2017 | Different regions including North Africa | Effects of climate change on the spatial distribution of I. ricinus | Primary occurrence records for I. ricinus | Not applicable | 2050 and 2070 | Observed and projected Temperature, precipitation | Ecological niche modeling, future climate change scenarios | Present and future potential distributions of I. ricinus showed overlap in the region |
| Amro et al., 2017 | Lybia | Description of eco-epidemiological parameters of CL and spatiotemporal distributions of CL cases | A total of 312 CL patients | A total of 312 reported patients | The armed conflict period from January 2011 till December 2012 | Demographic data. Date of infection, age, gender place residence, number and location of lesions, and treatment response were documented. Household members previously diagnosed with CL, presence of rodents, and sandflies in the patient’s neighborhood | PCR–RFLP approach targeting the ITS1 region of the rDNA. Correlative modeling approach | Coastal regions have a higher level of risk. Future projection of CL until 2060 showed a trend of increasing incidence of CL in the northwestern part of the country. A spread along the coastal region and a possible emergence of new endemics in the north-eastern districts of the country |
| Bauer et al., 2017 | Thirty-two countries including Tunisia | To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder | Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries | A total of 7392 patients with bipolar disorder | 2012, 2014, 2017 | Solar insolation, birth-cohort, family history, polarity of first episode, country physician density | Diagnosis of bipolar disorder according to DSM-IV criteria from a psychiatrist, direct questioning, reviewing records, or both | A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders |
| Hmamouch et al., 2017 | Boulemane Province, Morocco | Distribution of CL in the study area | A total 1009 reported cases of CL | A total of 1009 reported patients | 2000 to 2015 | Poverty, vulnerability, population density, urbanization, and bioclimatic factors | PCR–RFLP method targeting the ITS1 of ribosomal DNA of leishmania. Ordinary least squares regression (OLSR) | Saharan microclimate, characterized by the presence of |
| Horton et al., 2017 | Twenty hospitals in Egypt, Jordan, Oman, Qatar, and Yemen. Ten infectious disease hospitals in Egypt | Sentinel surveillance for SARI (Severe Acute Respiratory Infections) | Nasopharyngeal and oropharyngeal swabs | Patients meeting SARI case definitions | December 2007 through February 2014 | Climatic seasonality | Samples were tested by real time reverse transcriptase polymerase chain reaction (rtRT-PCR), MagMAX™ Pathogen RNA/DNA Kit. The chi-squared test. Logistic regression | Monthly variation, indicating seasonal differences in levels of infection, was observed for all pathogens. Viral respiratory pathogens are common among SARI patients in the Eastern Mediterranean Region |
| Talmoudi Khouloud et al., 2017 | Three rural areas in the governorate of Sidi Bouzid in Tunisia | Relationship between ZCL occurrence and possible risk factors Apredicting model for ZCL's control and prevention purposes | Monthly reported ZCL cases | The 1019 reported ZCL cases | 2009 to 2015 | Temperature, rainfall, relative humidity, wind speed, rodents’ density | Generalized additive model (GAM). Generalized additive mixed models (GAMM). Generalized cross-validation (GCV) score and residual test | Rodent density, average temperature, cumulative rainfall, and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence in the region |
| H.Trablesi et al., 2017 | Tunisia | Frequency of allergic asthma attacks | The stages of asthma of patients | Forty-nine patients with allergic asthma hospitalized in Pneumology department. The environmental study was conducted for 30 patients in their homes | February 2014–October 2014 | Dust, humidity, cold, heat, climate change, seasonality | Epidemiological and environmental survey for fungal flora. Statistical analyses SPSS, Chi2tests, two tailed | The frequency of attacks was significantly associated with the seasonality, which was closely related to climate ( |