Abstract
There is a global concern regarding the occurrences of harmful algal blooms (HABs) and their effects on human health. Lake Victoria (LV) has been reported to face eutrophication challenges, resulting in an increase of bloom-forming cyanobacteria. This study is aimed at understanding the association of HABs and health risks at Ukerewe Island. A cross-sectional study conducted on 432 study subjects and water samples for cyanobacteria species identification were collected at LV shores. The results reveal that concentrations of cyanobacteria cells are beyond (WHO) acceptable limits; species of Microcystis aeruginosa range from 90,361.63 to 3,032.031.65 cells/mL and Anabaena spp. range from 13,310.00 to 4,814,702 cells/mL. Water usage indicates that 31% use lake water, 53% well water and 16% treated supplied pipe water. Vomiting and throat irritation was highly reported by lake water users as compared to wells and pipe water (P < 0.001). Gastrointestinal illness (GI) was significantly elevated among lake water users as compared to pipe and well water users (P < 0.001). Visible blooms in lake water were associated with GI, skin irritation and vomiting as compared to water without visible blooms (P < 0.001). The concentration of cyanobacteria blooms poses greater risks when water is used without treatment.
INTRODUCTION
Cyanobacteria blooms have some toxin producing species which pose a potential health hazard to humans and other living organisms, and the risk is high when eutrophication occurs in fresh waters. Lake Victoria (LV), being a fresh water lake, has faced eutrophication challenges, resulting in an increase of bloom forming cyanobacteria throughout the year with the ability to produce hazardous cyanotoxins (Mbonde et al. 2004). Harmful algal blooms (HABs) can be visible as excessive scum of algal biomass on top of fresh water, which may be attributed to an increase in the levels of nitrogen and phosphorus in fresh water bodies, and this has been observed in Lake Victoria (Mchau et al. 2019). This increase in algal biomass causes low oxygen levels in the water which leads to the mortality of aquatic organisms, as well as reducing the quality of water for human consumption.
The toxins produced by cyanobacteria are classified on the basis of the symptoms observed in humans and other vertebrates, namely hepatotoxins, neurotoxins and irritant-dermal toxin. Microcystin (MC) produces hepatotoxins such as MC-LR, MC-RR and MC-YR, which often contaminate drinking water (Carmichael et al. 2001). The World Health Organization (WHO) has therefore proposed a provisional guideline for an acceptable limit of MC-LR concentration in drinking water of 1.0 μg/L (WHO 2003). In addition, cyanobacteria blooms create a threat to recreational water by producing harmful toxins and malodorous compounds as well as causing hypoxia and disruption of food webs in the ecosystem (Cheung et al. 2013). The occurrence of toxigenic cyanobacteria Anabaena and Microcystis, which produce cyanotoxins such as MC-LR, MC-RR and MC-YR, has been documented in all the countries that share the lake Victoria shores, namely Kenyan, Ugandan and Tanzania (Okello et al. 2010; Sitoki et al. 2012).
Human diseases due to cyanobacteria vary based on related exposure such as swimming, skin contact, bathing, and drinking. Several acute symptoms have been reported in humans such as stomach upset, vomiting, skin irritation, nausea, diarrhea, fever, throat irritation, headache, mouth blisters, muscle and joint aches, eye irritation, and allergic reactions (Kibria 2016). Chronic health effects include the possible human carcinogen for liver and colorectal malignancies. The International Agency for Research in Cancer (IARC) has categorized MC-LR as a causative factor for chronic illness (IARC 2010). Water ingestion has been identified as the major route of exposure to harmful cyanobacteria toxins in human and animals, which causes human health effects and animal deaths (Codd et al. 1994; Hilborn et al. 2014). However, few epidemiological studies have been conducted to document acute and chronic human health effects caused by cyanobacteria and cyanotoxin with regards to the route and modes of exposure (Chorus & Bartram 1999).
Globally, few countries have set up surveillance systems that monitor occurrences of HAB related illnesses as well as establishing country specific acceptable limits for the concentration of cyanobacteria cell density in waters used for different human activities. Instead they use the WHO set general guidelines which are not country specific. The World Health Organization (WHO) has proposed guidelines for different cell densities of cyanobacteria bloom levels and related illnesses, such as: for recreational waters cell densities of 20,000 cells/mL are associated with risk of short-term adverse health outcomes; and at a higher cell density of 100,000 cells/mL an additional risk for long-term illness exists. Cyanobacteria scum formation in bathing areas is associated with the risk of potential severe health outcomes such as throat irritation, stomach upset, skin irritation, vomiting, nausea, diarrhea, fever, and headache (WHO 2003). Due to the non-specific nature of the symptoms of HAB related illnesses and lack of specific guidelines for surveillance and diagnosis, it has proven to be difficult for health-care providers to identify and document HAB associated illnesses. This poses a serious public health omission in the identification of HAB related effects in human. Therefore, health-care providers should be aware of the HAB related symptoms as illness may present differently from other recreational water-associated illnesses and onset may occur soon after exposure such as headache, throat irritation, stomach upset, diarrhea, vomiting, skin and eye irritation to name but a few.
This study aims to identify the different species of cyanobacteria and their potential health effects that may be attributed to the existing dominant HAB species in Lake Victoria in the Ukerewe districts. Most of the HAB associated water illnesses are underestimated and go unrecognized due to lack of water quality assessment and disease surveillance systems that can record the water quality parameters as recommended by WHO and monitor illness related to cyanobacteria blooms. This study will document health related effects of HABs on the population of Ukerewe Island which mostly depend on the lake water for their daily human consumption. The documented information can be used to develop evidence-based HAB related illness prevention strategies.
METHODS
A cross-sectional study was conducted at Ukerewe district (Island), Mwanza region in Tanzania. A total of 432 subjects were recruited in December 2018. The study subjects were individuals who have been residing in the district for more than five years and were above the age of 18 years. The study protocol was adopted and modified from a water quality and associated illness study carried out in the USA by Wade et al. (2008) and Collier et al. (2015).
Water samples for cyanobacteria species identification were collected from selected sites at the lake Victoria shore in Ukerewe district, where water is fetched for different domestic purposes and recreation activities take place. Semi-structured questionnaires were used to collect information from all study subjects on demographic information, practices on water utilization and observed illness after exposure. The National Institute for Medical Research (NIMR) ethical committee reviewed the protocol for this study and granted ethical clearance number NIMR/HQ/R.8a/Vol. IX/2426.
Study site
Ukerewe District comprises 27 islands within Lake Victoria, in Mwanza region, northern Tanzania between latitudes 10°45′ and 20°15′ S and longitudes 320°45′ and 330°45′ E. Lake Victoria is the world's second largest freshwater body, measured by surface area, and the largest in the developing world, with a surface area of 68,800 km2 and a catchment covering 284,000 km2. Water samples were collected at eight different sites along the Lake Victoria shore, namely Lugenzi, Water Agency Street, Namagondo, Barazani, Bugolora, Nebuye, Kahama and Galu beach.
Water sample collection and Phytoplankton identification
Health effect assessment
Health effects were self-reported by the study subjects, based on the following definition: Having diarrhea was considered when an individual reported having three or more loose stools in a 24-hour period; vomiting; ejection of stomach contents through the mouth, stomach upset; disorder of digestive system functions characterized by discomfort or nausea. All the three symptoms together (diarrhea, vomiting and stomach upset) were regarded as gastrointestinal illness (GI) that interferes with regular activities. Skin irritation was defined as a state of inflammation, itching or painful reaction of the skin; eye irritation was either eye itching, eye infection or watery eyes and throat irritation was defined as pain, itchiness of the throat that can lead to cough, runny nose, or cold as general upper respiratory illness (URI) (Wade et al. 2008; Collier et al. 2015).
Statistical methods
Data were collected through an open data kit (ODK) which was then exported to Microsoft Excel (MS). Analysis was carried out using Epi Info Version 7.2.1.0. The outcome of interest was the observed health effects such as skin irritation, vomiting, diarrhea, stomach upset, and throat and eye irritation. Each outcome of interest was independently tested in Univariate analysis using a 2 × 2 and Chi-square–Mantel-Haenszel (2-tailed P-value) was used to determine the level of significance for the outcome of interest response with less than five in the 2 × 2 table. The Fisher exact test was used to determine the level of significance. All statistically significant outcome variables in the univariate analysis were further put together in the multivariate analysis.
Multivariate analysis was carried out by a backward method where the outcome with the weakest association was removed in the model sequentially until the best-fit model was realized. In the univariate analysis crude odds ratio and their 95% confidence intervals were reported, while in the multivariate analysis adjusted odds ratio with their 95% confidence intervals were reported. The results were considered significant when the P-value was less than 0.05.
RESULTS
During this study, while collecting the samples the water colour was observed to be greenish with bloom on the surface, which was a clear indication that cyanobacteria member dominated the areas, four main groups (classes) of phytoplankton were found, namely Chlorophyceae, Cyanophyceae, Bacillariophyceae and Dinophyceae (Table 1). The results indicate that cyanobacteria (Cyanophyceae) were blooming in all eight sites and they formed more than 97% of all phytoplankton in the lake. The most common members were Microcystis, Anabaena, Merismopedia, the concentration of Microcystis aeruginosa ranged from 90,361.63 to 3,032,031.65 cells/mL and among the eight sample collection sites five (62.5%) had above 100,000 cells/mL and three (37.5%) had less than 50,000 cells/mL. Anabaena spp. cells concentration ranged from 13,310 to 4,814,702 cells/mL, of which seven (87.5%) sites had above 100,000 cells/mL and one (12.5%) had less than 100,000 cells/mL. Merismopedia spp. cells concentration ranged from 2,843.69 to 201,113.04 cells/mL where only two (25%) sites had cells above 100,000 cells/mL and six (75%) sites had less than 100,000 cells/mL (Table 1). Well and treated pipe water were not tested for availability of cyanobacteria.
List of Phytoplankton species found at seven selected Lake Victoria lake shores . | |||||||||
---|---|---|---|---|---|---|---|---|---|
Taxa . | Selected sites along Lake Victoria shores . | ||||||||
Chlorophyceae . | Unit . | Lugenzi . | Water Agency St. . | Namagobo . | Barazani . | Bugolora . | Nebuye . | Kahama . | Galu Beach . |
(Green algae) . | |||||||||
Ankistrodesmus sp. | cells/mL | 90.25 | 150.9 | 75 | 33.85 | 22 | 10 | 21 | 80 |
Coelastrum microporum | cells/mL | 0 | 12.10 | 33.85 | 0 | 33.85 | 4 | 2 | 13 |
Pediastrum sp. | cells/mL | 0 | 0 | 0 | 33.85 | 0 | 0 | 0 | 0 |
Scenedesmus spp. | cells/mL | 0 | 0 | 0 | 135.41 | 270.83 | 1,218.72 | 1,624.96 | 3,656.16 |
Staurastrum spp. | cells/mL | 0 | 0 | 0 | 0 | 33.85 | 0 | 0 | 0 |
Cyanophyceae cyanobacteria | |||||||||
Anabaena spp. | cells/mL | 677,068.00 | 4,814,702.00 | 142,316.75 | 174,054.31 | 112,310.00 | 67,321.00 | 73,292.00 | 13,310.00 |
Chroococcus dispersus | cells/mL | 32 | 42.00 | 812.48 | 12 | 812.48 | 31 | 11 | 54 |
Merismopedia spp. | cells/mL | 2,843.69 | 201,113.04 | 2,843.69 | 1,421.84 | 2,447.60 | 4,361.00 | 32,562.00 | 189,815.90 |
Microcystis aeruginosa | cells/mL | 90,361.63 | 3,032,031.65 | 148,139.02 | 111,239.53 | 136,104.03 | 92,302.00 | 104,032.00 | 154,212.00 |
Microcystis flos aquae | cells/mL | 14,387.70 | 443,507.30 | 10,156.02 | 5,078.01 | 8,463.34 | 100,950.78 | 100,239.86 | 203.12 |
Microcystis spp. | cells/mL | 110 | 21,202.20 | 302 | 13,541.36 | 6,770.68 | 321 | 2,761.00 | 5,211.00 |
Planktolyngbya circumcreta | filament/mL | 118.49 | 0.00 | 67.71 | 50.78 | 78.98 | 0 | 0 | 0 |
Planktolyngbya spp. | filament/mL | 50.78 | 0 | 169.27 | 50.78 | 0 | 0 | 0 | 0 |
Bacillariophyceae diatoms | |||||||||
Aulacoseira spp. | cells/mL | 1,692.50 | 1,4026.70 | 1,777.30 | 4,824.11 | 761.7 | 0 | 0 | 3,046.80 |
Cyclotella spp. | cells/mL | 84.63 | 308.13 | 67.71 | 50.78 | 67.71 | 101.56 | 203.12 | 541.62 |
Fragilria spp. | cells/mL | 33.85 | 0 | 50.78 | 67.71 | 33.85 | 0 | 101.56 | 372.32 |
Navicula spp. | cells/mL | 0 | 0 | 67.71 | 0 | 67.71 | 101.56 | 101.56 | 101.56 |
Nitzschia acicularis | cells/mL | 1,263.85 | 0.00 | 1,218.72 | 220.05 | 327.23 | 0 | 0 | 203.12 |
Synedra cunningtonii | cells/mL | 440.09 | 210 | 293.37 | 84.63 | 67.71 | 0 | 0 | 0 |
Dinophyceae | |||||||||
Glenodinium spp. | cells/mL | 0 | 0 | 0 | 203.12 | 33.85 | 0 | 0 | 0 |
List of Phytoplankton species found at seven selected Lake Victoria lake shores . | |||||||||
---|---|---|---|---|---|---|---|---|---|
Taxa . | Selected sites along Lake Victoria shores . | ||||||||
Chlorophyceae . | Unit . | Lugenzi . | Water Agency St. . | Namagobo . | Barazani . | Bugolora . | Nebuye . | Kahama . | Galu Beach . |
(Green algae) . | |||||||||
Ankistrodesmus sp. | cells/mL | 90.25 | 150.9 | 75 | 33.85 | 22 | 10 | 21 | 80 |
Coelastrum microporum | cells/mL | 0 | 12.10 | 33.85 | 0 | 33.85 | 4 | 2 | 13 |
Pediastrum sp. | cells/mL | 0 | 0 | 0 | 33.85 | 0 | 0 | 0 | 0 |
Scenedesmus spp. | cells/mL | 0 | 0 | 0 | 135.41 | 270.83 | 1,218.72 | 1,624.96 | 3,656.16 |
Staurastrum spp. | cells/mL | 0 | 0 | 0 | 0 | 33.85 | 0 | 0 | 0 |
Cyanophyceae cyanobacteria | |||||||||
Anabaena spp. | cells/mL | 677,068.00 | 4,814,702.00 | 142,316.75 | 174,054.31 | 112,310.00 | 67,321.00 | 73,292.00 | 13,310.00 |
Chroococcus dispersus | cells/mL | 32 | 42.00 | 812.48 | 12 | 812.48 | 31 | 11 | 54 |
Merismopedia spp. | cells/mL | 2,843.69 | 201,113.04 | 2,843.69 | 1,421.84 | 2,447.60 | 4,361.00 | 32,562.00 | 189,815.90 |
Microcystis aeruginosa | cells/mL | 90,361.63 | 3,032,031.65 | 148,139.02 | 111,239.53 | 136,104.03 | 92,302.00 | 104,032.00 | 154,212.00 |
Microcystis flos aquae | cells/mL | 14,387.70 | 443,507.30 | 10,156.02 | 5,078.01 | 8,463.34 | 100,950.78 | 100,239.86 | 203.12 |
Microcystis spp. | cells/mL | 110 | 21,202.20 | 302 | 13,541.36 | 6,770.68 | 321 | 2,761.00 | 5,211.00 |
Planktolyngbya circumcreta | filament/mL | 118.49 | 0.00 | 67.71 | 50.78 | 78.98 | 0 | 0 | 0 |
Planktolyngbya spp. | filament/mL | 50.78 | 0 | 169.27 | 50.78 | 0 | 0 | 0 | 0 |
Bacillariophyceae diatoms | |||||||||
Aulacoseira spp. | cells/mL | 1,692.50 | 1,4026.70 | 1,777.30 | 4,824.11 | 761.7 | 0 | 0 | 3,046.80 |
Cyclotella spp. | cells/mL | 84.63 | 308.13 | 67.71 | 50.78 | 67.71 | 101.56 | 203.12 | 541.62 |
Fragilria spp. | cells/mL | 33.85 | 0 | 50.78 | 67.71 | 33.85 | 0 | 101.56 | 372.32 |
Navicula spp. | cells/mL | 0 | 0 | 67.71 | 0 | 67.71 | 101.56 | 101.56 | 101.56 |
Nitzschia acicularis | cells/mL | 1,263.85 | 0.00 | 1,218.72 | 220.05 | 327.23 | 0 | 0 | 203.12 |
Synedra cunningtonii | cells/mL | 440.09 | 210 | 293.37 | 84.63 | 67.71 | 0 | 0 | 0 |
Dinophyceae | |||||||||
Glenodinium spp. | cells/mL | 0 | 0 | 0 | 203.12 | 33.85 | 0 | 0 | 0 |
Reported health effects from the study area
The study was conducted in December 2018, and a total of 432 subjects participated. The mean age was 42 years old with a range of 18–86 years old, 234 (54%) were male and 198 (46%) female. One hundred and thirty-four subjects (31%) reported using lake water as their main source of water, while 229 (53%) used well water and 69 (16%) used treated supplied pipe water as their main source of water for drinking and other domestic uses.
Reported health effects among the subjects were as follows: 78 (18.06%) did not report any health effects while 71 (16.44%) reported one health effect, 81 (18.75%) reported two health effects, 124 (28.70%) reported three health effects, 62 (14.35%) reported four health effects, 12 (2.78%) reported five health effects and four (0.98%) reported all six health effects. The study observed that there is a mixture of water uses and different exposure whereby a person can use pipe water for drinking purposes but use lake water for bathing and other water activities and vice versa. More than 50% of the subjects reported skin irritation, stomach upset and eye irritation followed by diarrhea (32%) while vomiting (9%) and throat irritation (10%) were least reported.
In univariate analysis, individuals who used the lake as their source of drinking water were six times more likely (OR 6.1, 95% CI 2.8–13.58) to have vomiting compared to those individuals who used wells as their source of drinking water and this was statistically significant (P < 0.001). The odds of getting throat irritation when using the lake as a source of drinking water were six times higher than when using wells as a source of drinking water OR = 6.57 (95% CI = 2.74–15.79, P < 0.001).
Those who had used the lake as their source of drinking water were observed to be associated with more stomach upsets (OR = 8.4, 95% CI = 4.49–14.78, P < 0.001) compared to those using wells as their source of drinking water. The risk of vomiting when an individual consumed lake water was observed to be 17-fold higher compared to when an individual consumed treated supplied piped water (95% CI = 2.28–127.2) and this was statistically significant (P < 0.001). Bathing using treated supplied pipe water was protective against eye irritation as compared with the contaminated lake water source with cyanobacteria (OR = 0.46, 95% CI = 0.24–0.85) and this was statistically significant (P = 0.01). Getting a stomach upset when an individual used lake water for drinking was 45.2-fold higher than when they used treated supplied pipe water for drinking and this was statistically significant (95% CI = 19.78–111.81, P < 0.001).
The odds of vomiting when consuming water with visible bloom was almost four times higher compared to drinking water without visible bloom, which was statistically significant (95% CI = 1.49–10.44, P = 0.003). The odds of getting diarrhea when drinking water with visible bloom is two-fold higher as compared with consuming water source with no visible bloom (95% CI = 1.39–3.6 and P < 0.001).
The odds of getting skin irritation among those individuals using water with visible bloom was almost two times higher compared to those who used water for bathing without visible bloom (95% CI = 1.0–2.3, P = 0.04). Study subjects who reported drinking water with visible bloom were four times more associated with throat irritation than those who consumed water without visible bloom (OR = 4, 95% CI = 1.37–11.8, P = 0.006). The study showed that the likelihood of getting stomach upset when consuming water with visible bloom was three-fold higher than those who consumed water with no visible bloom and this was statistically significant (OR = 3.4, CI = 2.28–5.28, P < 0.001).
The study subjects' occupation was compared between fishermen and those employed with non-fishing activities. Individuals who were in the fishing activities were more likely to have reported symptoms of vomiting as compared with their counterparts who were involved in non-fishing activities (OR = 2, 95% CI = 1–4.5, P = 0.02). This study indicated that fishermen were twice as likely to report symptoms of diarrhea as compared to those in other non-fishing occupations (95% CI = 1.2–3.3, P = 0.003). The odds of getting skin irritation among fishermen were almost two-fold higher (95% CI = 1–2.9, P = 0.02) as compared with individuals in other non-fishing occupations.
Study subjects with fishing occupations were more than twice as likely to have throat irritation as compared to those with non-fishing occupations (OR = 2.4, 95% 1.1–5.1, P = 0.02).
Diarrhea and throat irritation were reported to be mainly associated with the consumption of more than 1 L of lake water (OR = 2, 95% CI = 1–2.4, P = 0.02 and OR = 4, 95%CI = 2.11–8.9, P < 0.001 respectively).
DISCUSSION
Based on WHO guidelines, cyanobacteria cell concentration at 20,000 cells/mL is associated with a risk for short-term adverse health outcomes and at 100,000 cells/mL the risk for long-term illness exists; potentially severe health outcomes (WHO 2003). The observed levels of cyanobacteria's scum concentration in this study are very high and utilization of water from the lake without treatment may lead to acute and chronic health problems. The predominance of cyanobacteria in the plankton of Lake Victoria has been linked with eutrophication of the lake that may be caused by excessive nutrients such as nitrogen and phosphorus nutrient (Hecky 1993; Mchau 2019). Other studies have indicated that the occurrence of Anabaena and Microcystis species in higher abundances in Lake Victoria has threatened the water quality due to the ability of these species to produce toxins (Sekadende et al. 2005; Mbonde et al. 2015). The dominant species of cyanobacteria observed in this study, such as Anabaena and Microcystis, may be a threat to aquatic organisms and pose a potential health risk to humans when water from the lake is consumed without treatment (Chorus & Bartram 1999; Semyalo et al. 2010).
Toxin produced by Microcystis, Anabaena and Merismopedia and their health effects
The observed dominant cyanobacteria of genera Anabaena, Merismopedia and Microcystis can produce variants of Microcystin toxin that can lead to hepatotoxicity, which inhibits eukaryotic protein phosphatases in human. These toxins have potential health effects such as gastrointestinal illness, liver inflammation, and hemorrhage and liver failure leading to death, pneumonia, and dermatitis (Chorus et al. 2000; Boopathi & Ki 2014). Anabaena spp. can also produce Cylindrospermopsin toxins that are hepatotoxic, cytotoxic, and neurotoxic, which will inhibit glutathione synthesis, protein synthesis and cytochrome P450 in humans. Cylindrospermopsin toxin has the following health effects: pneumonia, liver inflammation, and hemorrhage, gastrointestinal and dermatitis (Carmichael 2001). Anatoxin-a toxins are one of the cyanobacteria toxins which are produced by Anabaena spp. and lead to neurotoxicity and imitation of the neurotransmitter acetylcholine. Anatoxin-a toxins can cause a number of health effects including: tingling, burning, numbness, drowsiness, incoherent speech, and respiratory paralysis leading to death. The observed dominant Anabaena spp. in the lake can potentially produce Saxitoxin, which causes neurotoxicity and blockage of voltage-gated Na+ channels in humans and other vertebrates. The toxin can cause numbness, burning, tingling, drowsiness, incoherent speech and respiratory paralysis leading to death (Funari & Testai 2008; Boopathi & Ki 2014). Apart from the chronic health effects, the dominant species can potentially cause acute symptoms such as stomach upset, vomiting, skin irritation, nausea, diarrhea, fever, throat irritation, headache, mouth blisters, muscle and joint aches, eye irritation, and allergic reactions (Kibria 2016).
Health effects reported from different water sources utilization
The assessment of water consumption among study subjects shows that 31% use lake water as the main source of water, 53% use well water and 16% used treated supplied pipe water as the main water source for drinking and domestic purposes. The subjects reported vomiting as one of the health effects occurring after drinking water from the lake source, which is infested with cyanobacteria. The risk of vomiting is 6.1-fold higher compared to those accessing drinking water from wells (P < 0.001). The risk of vomiting when consuming bloom contaminated water is 17-fold compared to treated supplied pipe water (P < 0.001; see Table 2). The same finding that cyanobacteria infested water can cause vomiting was reported in the UK (Turner et al. 1990) and in Australia (Pilotto et al. 1997). Vomiting was still statistically significant in multivariate analysis (P < 0.05; Table 2). The odds of getting throat irritation when drinking cyanobacteria contaminated water from the lake source is 6.57 higher than when drinking from the wells (P < 0.001), and this association was also strong in multivariate analysis (P < 0.05; Table 2). Throat irritation is one of the documented health effects after ingestion of algal bloom contaminated water in most recreational activities or water related exposure (Kibria 2016).
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Water source . | Yes . | No . | cOR (95% CI) . | P value . | AOR (95% CI) . | P value . |
Vomiting | Lake | 27 | 107 | 6.1 (2.8–13.58) | <0.001 | 2.8 (1.18–6.4) | 0.01 |
Wells | 9 | 220 | |||||
Diarrhea | Lake | 48 | 86 | 1.5 (0.95–2.38) | 0.08 | ||
Wells | 62 | 167 | |||||
Skin irritation | Lake | 80 | 54 | 1.21 (0.78–1.86) | 0.3 | ||
Wells | 126 | 103 | |||||
Eye irritation | Lake | 69 | 65 | 0.86 (0.56–1.33) | 0.5 | ||
Wells | 126 | 103 | |||||
Throat irritation | Lake | 23 | 111 | 6.57 (2.74–15.79) | <0.001 | 4.3 (1.5–11.76) | 0.004 |
Wells | 7 | 222 | |||||
Stomach upset | Lake | 119 | 15 | 8.14 (4.49–14.78) | <0.001 | 7.7 (4.2–14.4) | <0.001 |
Wells | 113 | 116 | |||||
Vomiting | Lake | 27 | 107 | 17 (2.28–127.2) | <0.001 | ||
Pipe | 1 | 68 | |||||
Diarrhea | Lake | 48 | 86 | 1.19 (0.64–2.2) | 0.5 | ||
Pipe | 22 | 47 | |||||
Skin irritation | Lake | 80 | 54 | 0.65 (0.35–1.2) | 0.16 | ||
Pipe | 48 | 21 | |||||
Eye irritation | Lake | 69 | 65 | 0.46 (0.24–0.85) | 0.01 | 0.2 (0.07–0.57) | 0.002 |
Pipe | 48 | 21 | |||||
Throat irritation | Lake | 23 | 111 | Undefined | 0.005 | ||
Pipe | 0 | 69 | |||||
Stomach upset | Lake | 119 | 15 | 45.2 (19.72–111.81) | <0.001 | 58.96 (21–162.73) | <0.001 |
Pipe | 10 | 59 |
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Water source . | Yes . | No . | cOR (95% CI) . | P value . | AOR (95% CI) . | P value . |
Vomiting | Lake | 27 | 107 | 6.1 (2.8–13.58) | <0.001 | 2.8 (1.18–6.4) | 0.01 |
Wells | 9 | 220 | |||||
Diarrhea | Lake | 48 | 86 | 1.5 (0.95–2.38) | 0.08 | ||
Wells | 62 | 167 | |||||
Skin irritation | Lake | 80 | 54 | 1.21 (0.78–1.86) | 0.3 | ||
Wells | 126 | 103 | |||||
Eye irritation | Lake | 69 | 65 | 0.86 (0.56–1.33) | 0.5 | ||
Wells | 126 | 103 | |||||
Throat irritation | Lake | 23 | 111 | 6.57 (2.74–15.79) | <0.001 | 4.3 (1.5–11.76) | 0.004 |
Wells | 7 | 222 | |||||
Stomach upset | Lake | 119 | 15 | 8.14 (4.49–14.78) | <0.001 | 7.7 (4.2–14.4) | <0.001 |
Wells | 113 | 116 | |||||
Vomiting | Lake | 27 | 107 | 17 (2.28–127.2) | <0.001 | ||
Pipe | 1 | 68 | |||||
Diarrhea | Lake | 48 | 86 | 1.19 (0.64–2.2) | 0.5 | ||
Pipe | 22 | 47 | |||||
Skin irritation | Lake | 80 | 54 | 0.65 (0.35–1.2) | 0.16 | ||
Pipe | 48 | 21 | |||||
Eye irritation | Lake | 69 | 65 | 0.46 (0.24–0.85) | 0.01 | 0.2 (0.07–0.57) | 0.002 |
Pipe | 48 | 21 | |||||
Throat irritation | Lake | 23 | 111 | Undefined | 0.005 | ||
Pipe | 0 | 69 | |||||
Stomach upset | Lake | 119 | 15 | 45.2 (19.72–111.81) | <0.001 | 58.96 (21–162.73) | <0.001 |
Pipe | 10 | 59 |
Gastrointestinal illness (GI) was significantly elevated among study subjects using water from the lake as compared to pipe and well water users. Getting stomach upsets when drinking cyanobacteria contaminated water from the lake source is 45.2 and 8.4-fold higher than drinking treated supplied pipe and well water respectively (P < 0.001). This finding was also reported by Hilborn et al. (2014) and Collier et al. (2015). The association between stomach upset and contaminated water was observed to be strong in multivariate analysis (P < 0.001). Bathing using treated supplied pipe water is protective against eye irritation as compared to contaminated lake water source with cyanobacteria (OR = 0.46, P < 0.05) and the observation was the same on multivariate analysis (P < 0.05). Acute and short-term health effects can be preventable with adequate treatment which significantly reduces cyanobacteria cell numbers by up to 99%, hence making the water safe for human use (Dietrich & Hoeger 2005; Funari & Testai 2008). WHO reported that swimmers in water containing cyanobacteria may suffer from allergic reactions such as eye irritation (WHO 2014).
Bloom availability
The evidence that bloom was present during reporting of HAB related illness is important for proper linkage of disease related to HABs in the water. The scum of cyanobacteria may be visible at some time during the day and then disappears and therefore it was important to associate the health risk with the visible algal scum in the water. The study reveals the odds of vomiting when consuming water with visible bloom is almost four-fold compared to drinking water without visible bloom (P = 0.003). The likelihood of GI was higher when consuming water with visible bloom, and for diarrhea and stomach upset the chances were 2 and 3.4 respectively (P < 0.001) as compared with water sources with no visible bloom. The same finding was observed on multivariate analysis where diarrhea and stomach upset still had a statistically significant link with bloom availability (P < 0.001); previous research has reported the same (Stone & Bress 2007; Collier et al. 2015). The odds of reported skin and throat irritation among water users with visible bloom is almost two and four times higher than those using water without visible bloom respectively (P < 0.05; see Table 3). The Harmful Algal Bloom-related Illness Surveillance System (HABISS) of the USA reported an association of bloom availability in water with related illness for the year 2009–2010 (Hilborn et al. 2014).
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Variable . | Yes . | No . | cOR (95% CI) . | P value . | AOR (95%CI) . | P value . |
Vomiting | Bloom | 29 | 220 | 3.95 (1.49–10.44) | 0.003 | ||
No bloom | 5 | 150 | |||||
Diarrhea | Bloom | 85 | 164 | 2.25 (1.39–3.6) | <0.001 | 2.4 (1.5–4) | <0.001 |
No bloom | 29 | 126 | |||||
Skin irritation | Bloom | 159 | 90 | 1.5 (1–2.3) | 0.04 | ||
No bloom | 81 | 74 | |||||
Eye irritation | Bloom | 140 | 109 | 1.2 (0.8–1.8) | 0.36 | ||
No bloom | 80 | 75 | |||||
Throat irritation | Bloom | 24 | 225 | 4 (1.37–11.8) | 0.006 | ||
No bloom | 4 | 151 | |||||
Stomach upset | Bloom | 171 | 78 | 3.4 (2.28–5.28) | <0.001 | 3.39 (2.2–5.2) | <0.001 |
No bloom | 60 | 95 |
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Variable . | Yes . | No . | cOR (95% CI) . | P value . | AOR (95%CI) . | P value . |
Vomiting | Bloom | 29 | 220 | 3.95 (1.49–10.44) | 0.003 | ||
No bloom | 5 | 150 | |||||
Diarrhea | Bloom | 85 | 164 | 2.25 (1.39–3.6) | <0.001 | 2.4 (1.5–4) | <0.001 |
No bloom | 29 | 126 | |||||
Skin irritation | Bloom | 159 | 90 | 1.5 (1–2.3) | 0.04 | ||
No bloom | 81 | 74 | |||||
Eye irritation | Bloom | 140 | 109 | 1.2 (0.8–1.8) | 0.36 | ||
No bloom | 80 | 75 | |||||
Throat irritation | Bloom | 24 | 225 | 4 (1.37–11.8) | 0.006 | ||
No bloom | 4 | 151 | |||||
Stomach upset | Bloom | 171 | 78 | 3.4 (2.28–5.28) | <0.001 | 3.39 (2.2–5.2) | <0.001 |
No bloom | 60 | 95 |
Occupation risk and amount of water consumption
Occupation of the study subjects was compared between fisherman and other non-fishing activities, which includes employed, non-employed and farmers. Fishing is reported to be one of the risk activities of contracting health effects related to cyanobacteria bloom and cyanotoxin due to the frequency of water contact and usage during fishing activities. GI was strongly linked with the fishing occupation whereby vomiting and diarrhea were reported among fishermen as compared to non-fishermen (OR = 2, P < 0.05), vomiting and diarrhea shows a strong association in multivariate also (P < 0.05). Throat irritation was reported more by fishermen as compared to other occupations (P < 0.05; see Table 4). Studies conducted in China report the same higher risk for fishermen (Chen et al. 2009). The amount of water consumption was reported to be one of the factors that may contribute to reported health risk, whereby drinking more than 1 L is more of a risk than less than 1 L. Diarrhea and throat irritation were reported to be associated with the amount of water consumption where the likelihoods were two and four times more than these reported to consume less than 1 L respectively (P < 0.05); throat irritation had a strong link with the amount of water intake in multivariate analysis (P < 0.05; Table 5). The association of the amount of water ingested and the degree of illness was also reported in England, where soldiers become ill after ingesting bloom water with Microcystis spp. (Turner et al. 1990), and in the USA (Wade et al. 2008; Collier et al. 2015).
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Exposure . | Yes . | No . | cOR (95%CI) . | P value . | AOR (95%CI) . | P value . |
Vomiting | Fisherman | 13 | 77 | 2 (1–4.5) | 0.02 | 2.2 (1.05–4.4) | 0.03 |
Non-fisherman | 24 | 318 | |||||
Diarrhea | Fisherman | 40 | 50 | 2 (1.2–3.3) | 0.003 | 2 (1.2–3.2) | 0.004 |
Non-fisherman | 97 | 245 | |||||
Skin irritation | Fisherman | 63 | 27 | 1.8 (1–2.9) | 0.02 | ||
Non-fisherman | 194 | 148 | |||||
Eye irritation | Fisherman | 53 | 37 | 1.1 (0.7–1.8) | 0.5 | ||
Non-fisherman | 190 | 152 | |||||
Throat irritation | Fisherman | 11 | 69 | 2.4 (1.1–5.1) | 0.02 | ||
Non-fisherman | 19 | 323 | |||||
Stomach upset | Fisherman | 53 | 37 | 1.1 (0.7–1.9) | 0.53 | ||
Non-fisherman | 189 | 153 |
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Exposure . | Yes . | No . | cOR (95%CI) . | P value . | AOR (95%CI) . | P value . |
Vomiting | Fisherman | 13 | 77 | 2 (1–4.5) | 0.02 | 2.2 (1.05–4.4) | 0.03 |
Non-fisherman | 24 | 318 | |||||
Diarrhea | Fisherman | 40 | 50 | 2 (1.2–3.3) | 0.003 | 2 (1.2–3.2) | 0.004 |
Non-fisherman | 97 | 245 | |||||
Skin irritation | Fisherman | 63 | 27 | 1.8 (1–2.9) | 0.02 | ||
Non-fisherman | 194 | 148 | |||||
Eye irritation | Fisherman | 53 | 37 | 1.1 (0.7–1.8) | 0.5 | ||
Non-fisherman | 190 | 152 | |||||
Throat irritation | Fisherman | 11 | 69 | 2.4 (1.1–5.1) | 0.02 | ||
Non-fisherman | 19 | 323 | |||||
Stomach upset | Fisherman | 53 | 37 | 1.1 (0.7–1.9) | 0.53 | ||
Non-fisherman | 189 | 153 |
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Variable . | Yes . | No . | cOR (95%CI) . | P value . | AOR (95% CI) . | P value . |
Vomiting | Less than 1lt | 19 | 204 | 1 (0.5–2) | 0.88 | ||
>1lt | 17 | 192 | |||||
Diarrhea | Less than 1lt | 79 | 144 | 1.6 (1.06–2.44) | 0.023 | ||
>1lt | 53 | 156 | |||||
Throat irritation | Less than 1lt | 35 | 188 | 4 (2–7.7) | <0.001 | 3.3 (1.6–7) | 0.001 |
>1lt | 10 | 199 | |||||
Stomach upset | Less than 1lt | 121 | 102 | 0.86 (0.58–1.26) | 0.44 | ||
>1lt | 121 | 88 |
. | Response . | Univariate . | Multivariate . | ||||
---|---|---|---|---|---|---|---|
Health effect . | Variable . | Yes . | No . | cOR (95%CI) . | P value . | AOR (95% CI) . | P value . |
Vomiting | Less than 1lt | 19 | 204 | 1 (0.5–2) | 0.88 | ||
>1lt | 17 | 192 | |||||
Diarrhea | Less than 1lt | 79 | 144 | 1.6 (1.06–2.44) | 0.023 | ||
>1lt | 53 | 156 | |||||
Throat irritation | Less than 1lt | 35 | 188 | 4 (2–7.7) | <0.001 | 3.3 (1.6–7) | 0.001 |
>1lt | 10 | 199 | |||||
Stomach upset | Less than 1lt | 121 | 102 | 0.86 (0.58–1.26) | 0.44 | ||
>1lt | 121 | 88 |
CONCLUSIONS
The concentration of cyanobacteria blooms found in this study goes beyond the WHO acceptable limit whereby dangerous dominant cyanobacteria species of Microcystis aeruginosa range from 90,361.63 to 3,032.031.65 cells/mL and Anabaena spp. cells concentration range from 13,310.00 to 4,814,702 cells/mL. At this level water use from the lake source was found to be associated with acute health outcomes. The result indicates the potential health risk of using lake water without any treatment for human consumption. It is therefore advised to continue to monitor the water quality at Ukerewe area in order to understand its spatial and temporal dynamism of phytoplankton. The long-term study of Phytoplankton helps to understand the nature of nutrients or pollution entering the water body because phytoplanktons are a good and cheaper indicator of environmental change as compared to chemical indicators. The documented illness associated with cyanobacteria infested water can be used as a baseline to improve case detection in the district and contribute to the development of evidence-based prevention strategies to mitigate adverse health outcomes that may result in long-term exposure to HABs. It remains important to be able to identify and quantify the different types of cyanotoxin produced which exist in lake water. This will help to establish a long-term study that determines the chronic effect of persistence exposure of cyanotoxin.