Table 1.
A systematic review of the sampled countries’ literature to determine their vulnerabilities to the five significant climate change impacts: their exposure to climate drivers, the study location, and the potential resulting outcome from the exposure (see Appendix A). This was developed as a measure of the sampled country’s intensity to climate impacts on human health and the health systems’ preparedness against the impacts through the survey.
| Impacts | Author (Year) | Study Period (Year) | City/Country | Study Population | Study Design/Statistical Model | Exposure | Outcome |
|---|---|---|---|---|---|---|---|
| Water, sanitation, and water-borne diseases | [32] | 2012 | Jamestown/Agbogbloshie (Ghana) | 401 Households | Cross-sectional Descriptive, bivariate, and Multivariate | Floods | Reported cases of diarrheal diseases. A strong correlation between flooding and diarrheal disease. |
| [30] | 1990–2011 | North-West (Nigeria) |
Morbidity and mortality dataset on cholera cases | Ecological. Stepwise multiple regression, G.A.M. | Min/Max temp, annual Temp and RH | A significant correlation between cholera and annual min/max temperature and rainfall with 1716 deaths from 41,784 cases in 2010 in 18 states. | |
| [33] | 2012–2014 | Cape Town (South Africa) | Surveillance database on 58,617 children under five years. | Poisson regression | Min and Max temp | A 32% to 40% increase in diarrhoea incidence at 5 oC increase in Min and Max Temp. | |
| [34] | 2013–2015 | Amhara region (Ethiopia) |
Retrospective data on children under five years | Ecological Negative Binomial |
Average monthly Temp and rainfall | A monthly incidence rate of childhood diarrhoea at 11.4 per 1000 (95% Cl) was significantly associated with mean average temperature and rainfall. | |
| [72] | 1991–1993 | Hospital-Based (Malindi). (Kenya). | 862 children under five years old | Case-control Binary logistic regression |
Rainfall and Temperature | A strong positive correlation between rainfall, temperature, and childhood bloody diarrhoea. | |
| Vector-borne diseases. | [38] | 1995–2006 | National (Ghana) |
Reported cases of malaria ranging from 5054 to 347,000 per 100,000 | Ecological GLLMM and Local Moran’s I |
Rainfall, temperature, and humidity | A statistically significant correlation between temperature, humidity, and malaria incidence with a less significant association with rainfall as it only predicted malaria prevalence. |
| [39] | 1998–2008 | Ondo state (Nigeria) |
Data on weather variability; cases of malaria in 18 government hospitals | Ecological Poisson multiple regression |
Air and sea surface temp. | The occurrence of monthly malaria of 53.4% and 29% at 1 oC increase in air and sea surface temp. | |
| [40] | 1998–2017 | Mutale (Limpopo province) (South Africa) |
Malaria and climate data | Ecological Spearman correlation SARIMA |
Temp. Rainfall RH |
A positive significant association malaria incidence and total monthly rainfall, min and max temp., average temp., and mean relative humidity. | |
| [73] | 1989–2009 | Amhara, SNNPR, Tigray, Oromia (Ethiopia) | Data on cases of visceral leishmaniasis cases and meteorological data | Ecological Binary and multivariate regression |
Annual average Temp. and rainfall | 94.7% of Vl cases occurred between 20–37 °C of annual average Temp, with fewer cases with increasing rainfall. | |
| [74] | 2004–2014 | Baringo county. (Kenya) |
Malaria data from 10 health facilities; meteorological data | Ecological Negative binomial regression |
Rainfall and Temp. | Rainfall increased malaria transmission across four zones at a time lag of 2 months while temp. increased cases of malaria in riverine and highland zones at time lad of 0 and one month. | |
| Extreme weather events | [59] | Secondi-Takoradi (Ghana) |
207 heads of households | Mixed cross-sectional Descriptive analysis |
Floods | Report of psychological, environmental, and economic problems; disease outbreaks (malaria, cholera, and dysentery). | |
| (Eludoyin et al., 2013 [65] | 1951–2009; 2003–2012 | National Akure (Nigeria) |
Secondary data Data on the incidence of heat rash. |
Ecological Descriptive and correlation analysis |
Extreme temperature | Population experience of thermal stress since year 2000 and a significant heat rash among the population between September and December from 2003 to 2012. | |
| [55] | 2011–2012 | Ohangwena, Oshana, Omusata (Namibia) |
282 households | Cross-sectional | Floods | A remarkable but unspecified number of deaths, injuries, illness from resulting floods. | |
| [66] | 2006–2010 | Cape Town, Durban, J’berg (South Africa) |
Ambient temperature-all-cause mortality | Case-cross over epidemiological design G.A.M. |
Ambient Temp. | Increased temperature above the city-specific threshold significantly increased the general population risk of death (number not specified). | |
| [75] | 2009–2014 | National survey (Ethiopia) |
55,219 children under five years old | Meta-analysis Bayesian Poisson |
Drought | Minimal food-insecure areas showed elevated U5DR compared to stressed food-insecure areas as death rate increases as the prevalence of acute malnutrition increases. | |
| Nutrition, food security and distribution | [46] | 2016 | Bongo District (Ghana) |
246 Mother–child pairs (children under 5 years) |
Mixed-method cross-sectional Descriptive statistics |
Drought | Malnutrition and food insecurity resulted from drought impact, 97.2% being food insecure; children stunting (42.3%), underweight (24.4%) and wasting (17.5%). |
| [50] | 2015 | National data (Nigeria) |
Food and crop production index, population density, annual average temp, and rainfall. | Ecological Bivariate correlation and multiple regression |
Floods, drought, land use and cover change. | Country’s food deficit due to low agricultural production; hence the country’s dependence on food import. Malnutrition resulting from food insecurity. | |
| [76] | 2013–2014 | Dubana and Kwathehle (South Africa) |
Children between 24 and 59 months and their caregivers | Cross-sectional Spearman correlation |
Summer and winter season | Hunger due to food insecurity was reported in the summer rather than in the winter though their difference in food consumption score was not statistically significant. | |
| [54] | 2014 | All regions (Ethiopia) |
National F.A.O. dataset |
Ecological study | Drought | A frequent drought increased population food insecurity from 10% to 15%. | |
| [43] | 2009–2013 | Marsabit district (Kenya) |
Children under five years old; 924 households | Panel study Descriptive z-score |
Drought | Approximately 20% of the children under study were malnourished. | |
| Mental health and wellbeing | [60] | 2015 | Kwaebibrim (History of a flood), West Akyem (no history of a flood) (Ghana) |
400 respondents; 200 from each district | Retrospective cohort study Descriptive |
Floods | Flood victims more likely to experience symptoms of mental health problems than the non-victims. Reports of significantly higher levels of obsessive compulsion, depression, anxiety, and other global severity indexes. |
| [61] | 2012 | Urban areas affected by floods. (Nigeria) |
100 victims of flood-induced crime | Cross-sectional Descriptive analysis |
Flooding | Flood-induced crime harms human health and wellbeing with possible effects of anxiety, depression, social dysfunction, and loss of confidence. | |
| [21] | 2018 | National (South Africa) |
Whole population | Systematic review | Extreme weather events | Population affected by multiple health and social stressors. |
Source: From authors.