Abstract: Urinary schistosomiasis is a serious disease in Cross River State, Nigeria. Dearth of information on its distribution has hampered the implementation of focused control of the disease. The availability of a rapid method for mapping the disease necessitated this research to provide data for control of Urinary schistosomiasis in Cross River State, Nigeria. The study used a rapid validated school-based questionnaire method in mapping schistosomiasis. Geographical information system (GIS) software tools were used to produce a spatial map for prevalence of infection and areas at risk for urinary schistosomiasis in Cross River State. Data analysis with SPSS package revealed that 9,993 (10.2%) female and 10,328 (10.0%) male pupils in 218 schools passed blood in urine in one month out of 199,794 pupils interviewed. There was no statistically significant difference in the prevalence between male and female pupils with infection (p<0.005). The prevalence of urinary schistosomiasis using questionnaire method correlated positively with the filtration method used in determining the egg output (r = 0.71, p< 0.001). Endemic schools were distributed in thirteen Local Government Areas of Cross River State, Nigeria. Yala and Yakurr LGAs had the highest number of schools that reported schistosomiasis with 39(59%) and 13(59%), respectively. Odukpani LGA had the lowest prevalence of 1 (0.2%). The overall results showed a mean urinary schistosomiasis prevalence of 10.2% for Cross River State, Nigeria. The findings of this study would guide Government and other relevant agencies in the implementation of control strategies for the treatment of urinary schistosomiasis in Cross River State, Nigeria.
INTRODUCTION
Schistosomiasis is a parasitic disease that has plagued humanity for centuries; it is caused by a trematode or fluke of genus Schistosoma. The disease has some time ago been misconceived as the male equivalent of menstruation and has therefore been celebrated as the coming of age for young males in rural endemic communities (Amazigo et al., 1997). Increase in incidence of urinary schistosomiasis in sub-Saharan Africa has been attributed to proliferation of water impoundment schemes like irrigation and damming. Ignorance of the population living in endemic communities has also fueled the spread of urinary schistosomiasis (Adamu, 2010; Ekpo and Mafiana, 2004)
The disease is also considered as one of the most frequently occurring parasitic infections globally (Okon et al., 2007; WHO, 1985). About 200 million persons in 76 countries, mainly in sub- Saharan Africa are believed to be affected by schistosomiasis and a total of 600 million persons are at risk of contracting the disease globally (WHO, 1985). In Cross River State, most of the population is involved in agriculture. The environment is also conducive for the thriving of the snail intermediate host, these factors have contributed to the prevalence of S. haematobium (Ejezie et al., 1991). A national prevalence survey carried out in 1990/91 among school children aged 5 to 14 years, reported the presence of schistosomiasis in all 36 states of Nigeria including the Federal Capital Territory, Abuja, with an estimated number of 20 million people infected (Ekpo and Mafiana, 2004; NSCP, 1996). Schistosomiasis can be treated effectively by giving a single oral dose of praziquantel, the drug is effective against all the species of schistosomes. Chemotherapy with health education and provision of safe water sources can reduce transmission. Control of snail intermediate hosts of the disease is however of very limited value (NSCP, 1999). Effort has been targeted on urinary schistosomiasis (the most common and easily diagnosed) for control (WHO, 1985). However, the absence of reliable data on the distribution of the disease in a broad scale has hampered control of the disease. Therefore, identifying in broad scale, the distribution pattern of the disease is crucial. Geographical Information Systems (GIS) and its increasing use in the epidemiology and control of tropical diseases (Openshaw, 1996) coupled with a rapid validated school-based questionnaire provided an opportunity to investigate the distribution of urinary schistosomiasis at a broad scale in Cross River State for the purpose of planning control strategies.
The objective of this study was to display the spatial distribution of urinary schistosomiasis infection in Cross River State, Nigeria.
MATERIALS AND METHODS
Study Area: The study was carried out in Cross River State, Nigeria, situated within the tropics, between latitudes 5°32' and 4°27' North and longitude 7°50' and 9°28' East. All year round rainfall of about 350 mm occurs along the coastal area. Rainfall in the hinterland is between 120 and 200 mm annually with maximum precipitation occurring from July to September. Ambient temperatures remain high throughout the year (22.4°C to 33.2°C). Relative humidity is high (60-93%). The climate is tropical except for Obudu Plateau which has an altitude of 1,575.76 metres above sea level and has temperate climate. (Ottong et al., 2010). The State has a population of 2.8 million people (National Population Commission, 2010).
Data collection: Morbidity school based questionnaire adapted from (Ekpo and Mafiana, 2004) was used for the study. This was modified to allow for individual diagnosis and parasitological comparison. Questionnaire was first pre-tested in Biase, a urinary schistosomiasis endemic Local Government Area (LGA) (Etim et al., 1998) and Akpabuyo LGA, whose urinary schistosomiasis status was unknown. The questionnaire had a list of 4 symptoms of the disease (blood in stool, abdominal pain, blood in urine and fever) and 4 diseases (malaria, diarrhea, urinary schistosomiasis, skin disease). All the information in the questionnaire was written in English language. Advocacy was paid to the Cross River State Education and Health authorities to solicit for cooperation. The questionnaires were packaged for each LGA and left with the LGA onchocerciasis coordinator for each of the LGAs, in conjunction with the LGA Education Secretaries. These questionnaires were delivered to the schools through this medium. The survey was restricted to primary school children, as earlier studies indicated an insignificant prevalence among secondary school children (Mafiana et al., 2003). Ethical approval for the study was obtained from the ethical committee of the Cross River State Ministry of Health, Calabar, Nigeria.
Filtration method was used to see if there was correlation between questionnaire and presence of ova of S. haematobium in urine. This was done with 1520 pupils randomly selected from 76 schools. A 10 mL of urine specimen was collected from each selected pupil between 10.00 and 14.00 h and preserved with 1 mL of 40% formaldehyde. The urine samples were taken back to the laboratory and processed using standard urine filtration. A 10 mL of urine was filtered through Nuclepore paper filters. The deposits were stained with a drop of Lugol iodine and examined under light microscope for the presence of S. haematobium eggs.
Collection of coordinates: The geographical coordinates (Latitude and Longitude) of schools were determined using the following:
| • | The Gazette of Place name in Nigeria |
| • | Transcription from 1.150,000 scale topography maps of the State/LGAs |
| • | Using a hand-held Global Position System (GPS) |
A hand-held GPS, (Garmin 12XL, Garmin Corp, USA) was used to determine the latitude and longitude of the schools. The coordinates were collected in the school compound; the location was marked after allowing the satellite error to come to a distance of 3 to 5 m.
Data analysis: All data were double-entered and verified using Epi-Info software (version 6.04; Centers for Disease Control Prevention, Atlanta, GA) and analyzed using SPSS version 10.0 for Windows (SPSS Inc, Chicago, IL, USA). For analysis of infection data, only schools which returned completed questionnaire, were included. Descriptive statistics, including 95% confidence intervals (95% CI), Standard Deviation (SD) and Standard Error (SE) were calculated for disease prevalence and incidence in each LGA. Student T-test analysis was also used to compare differences among variables. ArcView GIS with Spatial Analyst GIS software were used for display of spatial data. The location of each school was linked to the parasitological data using unique schools identifier.
RESULTS
The study analyzed questionnaires from seven hundred and seventy eight schools out of 1121 schools in the State (69.4%), (Table 1).
| Table 1: | Questionnaire return rate by all the Local Government Areas (LGAs) surveyed in Cross River State |
| Table 2: | Age range and percentage prevalence of school children reporting blood in urine (urinary schistosomiasis) per Local Government Area in Cross River State, Nigeria |
A T-test analysis using the SPSS statistical software indicated that there was a significant difference in infection by age (p<0.05), infection was highest in children within the age range of 10-15 years (Table 2). The study showed a mean prevalence of 10.2% for reported “blood in urine” (Table 2).
In all, a total of 9,993 (10.2%) females and 10,328 (10.0%) male pupils out of the 199,794 pupils interviewed, reported passing blood in urine (Table 3). A T-test analysis of the results using the SPSS statistical software indicated that there was no significant difference in the infection rate amongst males and females interviewed (p>0.05). The mean prevalence for the LGAs showed that Odukpani LGA had the lowest positive respondents for blood in urine for male (0.5%) and females (0.1%). The highest respondents for blood in urine for male were in Obudu with 33.4% prevalence while the highest respondents for females were in Ogoja with 47.3% (Table 3). “Blood in urine” was used to classify the level of infection in each school into five groups, viz: No infection: 0, Light infection: 0.1-9.99%, Moderate infection: 10-24.9%, Heavy infection: 25-49.9%, Very heavy infection: >50% (Red Urine Study Group, 1995; WHO, 1985).
| Table 3: | Distribution of school children interviewed by sex, LGA and the prevalence rate for urinary schistosomiasis based on questionnaire analysis |
| Table 4: | Intensity of urinary schistosomiasis by blood in urine in Primary Schools per LGA in Cross River State, Nigeria |
Very heavy infection was reported in only 40 (5.1%) schools of the 778 schools interviewed. Heavy, moderate and light infections were variously reported in 97 (12.5%) , 56(7.2%) and 13(1.6%) schools respectively (Table 4).
The sensitivity, specificity and predictive values were calculated, in 76 randomly selected schools using a table of random numbers. A total of 1,520 pupils, 20 from each of the 76 schools were randomly selected and their urine tested using filtration method to detect eggs. The results of the filtration method revealed that the questionnaire had high sensitivity and specificity for detection of schools with infection when calculated using a method by, Trajstman (1979). Spearman rank correlation showed a highly significant association between blood in urine and urine filtration test (r = 0.71; p<0.01). The overall mean prevalence using the filtration laboratory techniques was 144 (9.47%) for both sexes (Table 5). A T-test analysis of the results using the SPSS statistical software indicated that there was no significant difference between infection rates using laboratory filtration techniques and questionnaire method (Tables 3 and 5).
The mean ova load for male and female pupils was 36 ova per 10 mL of urine in males and 29 ova per 10 mL of urine for females.
| Table 5: | Detection of mean ova of S. haematobium among selected children in some schools in Cross River State using the filtration laboratory technique |
The highest ova load was among pupils aged 11-15 years recording 43 ova per 10 mL of urine and 37 ova per 10 mL of urine in male and female respondents respectively (Table 5).
DISCUSSION
The present study was aimed at facilitating the control of schistosomiasis in Cross River State since one of the major constraints in the control of schistosomiasis remains dearth in systematic data to show the population at risk of the infection. The high sensitivity (0.856) and specificity (0.971) as well as a strong correlation (r = 0.71; p<0.01) between reported blood in urine and presence of ova in urine in the present study has further demonstrated that questionnaires can be used to rapidly map out areas prevalent with urinary schistosomiasis. The study further corroborates earlier findings by Lengeler et al. (2002a, b) that questionnaire method in mapping of schistosomiasis prevalence is a breakthrough. The questionnaire method has reduced budgets for mapping of areas with the disease as compared to parasitological methods. The present study has mapped out most of the areas prevalent for urinary schistosomiasis in Cross River State, Nigeria. Although Several reports in the past have demonstrated the occurrence of urinary schistosomiasis in Cross River State (WHO, 1985; Ejezie et al., 1991; Etim et al., 1998; Okon et al., 2007), detailed and widespread data to show areas endemic for the disease in the entire State were still lacking.
Blood in urine in this study has similarly been used in China by Zhou et al. (2001), in Ogun State Nigeria by Ekpo and Mafiana (2004), in Western Kenya, Western Cameroon and Tanzania by Brooker et al. (2001a, b, 2002) and also in Tanzania by Lengeler et al. (1991). Reported “blood in urine in the last one month” was used as a preferred diagnostic indicator to urinary schistosomiasis since it is easier for the pupils to remember having passed blood in urine than urinary schistosomiasis which was described in the local languages by teachers to the pupils. There were no local names for urinary schistosomiasis in areas where children answered negative to blood in urine. Thus, the use of reported blood in urine was considered more reliable. Mafe et al. (2001), Nnoruka (2006) and Ekpo and Mafiana 2004) also made similar observations in their studies in Niger, Imo and Ogun states respectively.
The ratio of male to female respondents in the present study was 1:1. The study revealed that both male and female children engaged in activities that brought them in contact with water. These included fetching water for domestic use, bathing and other recreational activities. The sex of children interviewed can be a limiting factor to outcome of the results when there is skewed distribution in favour of one sex (Partnership for Child Development, 1999). e.g, in cultures where female children are protected and prevented from activities that had water contact, outcomes could be biased if more females are interviewed. Menstruation and misconceptions that blood in urine is highly suggestive of a venereal disease and promiscuity are other reasons why female responses are often bias. In the present study, there was absolutely no bias in the ratio of male and female respondents.
Infection was highest in children within the age range 10-15 years; this is in agreement with findings by Okon et al. (2009) and Ekpo and Mafiana (2004) who had similar findings in their studies in Cross River and Ogun States, respectively. It was observed that these group of children spend much time swimming, washing or having other water contact activities. It was this frequent contact with snail infested water bodies that gave rise to the high infection amongst the children.
Infection intensity in the entire State ranged from moderate to very heavy in areas where infections were prevalent. Very heavy infections were reported in 40 (5.1%) schools out of the 218 schools interviewed while heavy infections were reported in 97(12.5%) schools. This probably corresponded with high settlement of people and involvement of the population in agricultural practices in these areas.
The point prevalence map showed that infection varied among schools, heavily infected schools were found around tributaries of rivers. It was also noticed that some schools with heavy infections were also surrounded with neighboring schools with medium, light infections or no infection demonstrating that urinary schistosomiasis transmission increased where conditions for transmission were most favorable.
Infection was found mostly in the Northern and Central parts of Cross River State. These areas corresponded with intensive agricultural practices especially rice paddies found in the swampy areas of this part of the State.
On the other hand, the southern part of the State which had Calabar Municipality and Calabar South, Bakassi, Akpabuyo, Akamkpa and a greater part of Odukpani LGAs, had no infection. The reasons could be due to improved water supply in recent years which discouraged populations from engaging in recreational activities in open fresh water bodies. More so, the salinity of the water bodies in the southern part of the State was high, because of the proximity of the Atlantic Ocean. High salinity was unfavourable for the survival of the snail intermediate host, Rollinson et al. (2001).
The findings of this study using questionnaires reported urinary schistosomiasis mean prevalence of 10.2%. While the filtration method used for laboratory analysis reported 9.4% mean prevalence. A high sensitivity and specificity as well as strong correlation has already been proven based on the correlation analysis. Similar studies by Okon et al. (2009) had earlier established a positive correlation value between self reported blood in urine and laboratory analysis in Adim community in Cross River State, Nigeria. Studies by Ekpo and Mafiana (2004) in Ogun State Mafe et al. (2001) in Niger State and Nnoruka (2006) in Imo State confirm similar results in other parts of Nigeria.
The study has mapped out areas endemic with urinary schistosomiasis in Cross River State. These areas included 218 (28%) schools who reported blood in urine out of the 778 schools investigated. Out of the 218 infected schools, 40 (5.1%) and 97(12.5%) had very heavy and heavy infection rates respectively. The areas with infection corresponded to areas engaged in extensive agricultural practices especially swamp rice farming.
CONCLUSION
The data generated from the study can be used in the implementation of a mass control strategy for urinary schistosomiasis in the State. The spatial map can also be used as a guide in development of water resources like construction of dams. The data from this study can serve as baseline for future evaluation of urinary schistosomiasis control programme in the state and as a monitoring tool to measure efficiency of control programme.