Version Changes
Revised. Amendments from Version 1
We have updated one table and one figure in the article, to reflect the distribution of cases of clinical malaria by age and clarified the aetiology of clinical malaria. The main changes are in the discussion section where we have added arguments indicating the relevance of our findings for public health. We have clarified the gaps in the literature which are filled by our study and why the findings from our study were unexpected, thence justifying the title as an unusual P. falciparum monoparasitaemia. We clarified the objectives of the study and made the discussion more robust. The conclusions from the study were also clarified
Abstract
Background: Malaria is caused by one of five currently known Plasmodium parasite species causing disease in humans. While modelling has provided information of the vector, the same is not entirely the case for the parasite. The World Malaria reports of 2014 to 2016 reported 100% of confirmed cases from Nigeria being due to Plasmodium falciparum. Generally, about 98% of cases of uncomplicated malaria in most regions surveyed in Nigeria recently is due to P. falciparum, with the remainder being due to P. malariae. This study aimed to determine the proportions of Plasmodium parasites causing uncomplicated malaria in Wamakko Local Government Area of Sokoto State, north-western Nigeria.
Methods: The study was a descriptive, cross-sectional study conducted during the rainy season and dry season in north-western Nigeria. The area has a ‘local steppe’ climate and Sudanian Savannah vegetation. Sampling was via multistage cluster sampling. Selected participants were examined for pallor, palpable splenomegaly and signs of complicated malaria. Blood samples were also taken for rapid diagnosis of malaria and thick and thin films to identify parasitaemia and the parasite species. Participants found to have malaria were treated with Artemether/Lumefantrine and those with complicated malaria were referred to the nearest hospital.
Results: We found a parasite prevalence of 34.8% overall, which was higher in the rainy season (49.3%) than in the dry season (20.2%). There was monoparasitaemia of Plasmodium falciparum throughout the study area, irrespective of the clinical status of the participant. Mapping of the parasite was extended throughout the Local Government Area and the State.
Conclusions: Despite the intermediate endemicity in the area. P. falciparum monoparasitaemia affirms theories of disappearance of other parasite species, either due to faltering control of P. falciparum or more efficient control of other species.
Keywords: Malaria, Nigeria, Plasmodium falciparum, PfPR2-10
Introduction
Malaria is caused by one of five currently known Plasmodium species causing diseases in humans. These are P. falciparum, P. vivax, P. ovale, P. malariae and P. knowlesi. Scientists have modelled the anopheles mosquito vector extensively based on its characteristics, but not for the parasite, it has been difficult to predict its preponderance and distribution, with notable exceptions 1. An absence of the Duffy antigen on red blood cells of West Africans has long been postulated to be responsible for the absence of P. vivax in these areas 2, but cases of P. falciparum, P. malariae and P. ovale, in order of decreasing occurrence, have been found. The World Malaria Reports of 2014 3 and 2015 4 reported 100% of confirmed cases in Nigeria as being due to P. falciparum. It is generally thought to account for about 98% of all malaria cases, with P. malariae accounting for the rest, often as a co-infection with P. falciparum 5. This figure likely over-estimates the proportion of cases as P. falciparum is responsible for most severe cases of malaria; these are the cases most commonly reported alongside confirmed cases of malaria, which are tracked by passive surveillance in Nigeria. It may also be because of limited expertise in identifying other species of Plasmodium.
Available data from across Nigeria shows a mixed picture; large areas across northern Nigeria in 1967/68 found an average proportion of 22% of malaria parasitaemia due to P. malariae in a study at a time when most of Nigeria was considered holoendemic for malaria. P. malariae was often seen in coinfection with P. falciparum, particularly among younger age groups. P. ovale was responsible for 5% of malaria infections, being more common in children under five years of age, and P.falciparum ranged between 84.4% and 90.5% across age groups 6. The proportion of P. malariae was high, probably because the data was obtained from a survey of both asymptomatic and symptomatic participants.
More recently, in 2010, prior to the commencement of nationwide LLIN distribution, a study including 4209 individuals in Jos, northern Nigeria, found a P. malariae rate as low as 1.6%, with P. falciparum responsible for 98.7% of infections, sometimes in co-infection with P. malariae 5. Children aged less than 10 years and all individuals in every third household were selected for this abridged malaria indicator survey (MIS). Crucially, however, no P. vivax or P. ovale species were seen either in this location or another in south-eastern Nigeria, which was shown to have a higher rate of P. malariae infections (around 30%) and lower rate of P. falciparum infections (68.1%) in a study also conducted in 2010 7. This study, however, included 2,936 individuals from 1400 clusters in Abia state, spread out across the state. Quality control measures in the identification of parasite species were implemented in the study, including a WHO-certified malaria microscopist, giving credibility to the results obtained 7. In south-western Nigeria, a study in Ikorodu in 2012 recruited 1,496 participants of all ages, which included 237 children under the age of five years and 509 children aged 15 years and below. Microscopy and DNA evaluation was used to determine parasite species, which found that 93.6% of participants had P. falciparum infection, with the remainder being P. malariae 8. This is in contrast to previous studies in 1976 around the same location in south-western Nigeria, which found that 13% to 16% of parasitaemia was due to P. malariae, with 62 to 76% being due to P. falciparum 9. These proportions were the age-group specific parasite prevalence in the study, which included mostly children aged five to ten years (1,500 participants) in an attempt to compare spleen and parasite rates among individuals with sickle cell trait and those with normal adult haemoglobin. It also found P. ovale in 2% to 3% of participants in 5–10 and 2–4 year age groups, respectively. These findings, although limited in scope, perhaps suggest a changing trend, with the disappearance of P. ovale from Nigeria over time. P. falciparum is an undisputed leader in all the studies performed. Its high proportion perhaps accounts for high rates of malaria-related anaemia in most studies, explained by the ability of the parasite to invade and destroy both young and senescent red blood cells 8, 10. Most of the data regarding the distribution of plasmodium is local and specific for locations where the studies are performed and the national estimates are mostly based on estimations. The knowledge needs to be updated constantly, in view of the changes over time, to help in appraising the efforts at controlling malaria.
We conducted this study to determine the true relative proportions of parasites causing clinical malaria in Sokoto, north-western Nigeria.
Methods
Ethical statement
Ethical approval was obtained from the Independent Ethics committee of Usmanu Danfoidyo University Teaching Hospital, Sokoto, Nigeria with ethical approval number UDUTH/HREC/2014/No. 246. Ethical approval was also obtained from the Independent Ethical committee of the Sokoto State Ministry of Health with the approval number SMH/1580/VIV. Permission was also obtained from the district heads of the included communities in the study to visit the communities.
Study setting
The study was conducted in Wamakko Local Government Area of Sokoto State, located in the north-western geopolitical zone of Nigeria. It has an area of 732.146km 2, with a projected population of 260,860 by 2019 11. It is located at coordinates 13°2′16″N 5°5′37″E. The geography of the area is predominantly flat plains with Sudan Savannah-type vegetation and it stands at an altitude of 292m above sea level, near to the confluence of the Sokoto and Rima rivers. Its climate is tropical, described as local steppe climate.
Study design
The study was a two–point, cross-sectional prospective descriptive study conducted during the rainy season and dry season. In April and November 2016, we screened and recruited participants simultaneously until we reached the target population.
We determined the minimum sample size using Cochran’s formula 12, assuming a prevalence of 50% based on a previous survey 13, and 500 participants gave a power of at least 80% to show reliable results.
Sampling technique
As is the norm for MIS’s, multistage cluster sampling in proportion to size was employed. The sample was stratified in two stages. First by the political wards and second by settlements. The samples were selected at each stratum independently. In the first stage, the strata were selected proportionate to their size. The details of the settlements are in the supplement number 1. The primary clusters were four randomly selected wards of the eleven political wards within the Local Government Area (LGA), with secondary clusters being eight settlements randomly selected from the four wards; proportionate to size, making up the total sample size. Based on the assumptions of a 70% response rate and that 80% of households include at least one child less than five years of age, in accordance with a previous Nigeria MIS in 2010 14, approximately 892 households were required to meet the target of at least 500 participants per season based on the assumptions stated earlier. This was surpassed by the estimated number of households within the eight settlements selected. All children in the secondary clusters who fulfilled the inclusion criteria, and whose parents consented to participate, were included in the study.
Sample population
Participants were visited at their homes and while in the house, after identifying the household head. They were provided with information regarding the study and all eligible children within the household invited to participate. Those who accepted to have the children in the household included in the study signed or thumb-printed the informed consent form. All children in the selected settlements who met the age criteria of two to 10 years, with or without symptoms of malaria, were recruited for the study, provided they had been residents of the study area for at least two weeks. They were, however, excluded if they were suspected to have taken any medication with antimalarial properties within the two weeks prior to enrolment 36. Recruitment was carried out on consecutive days until the entire village was covered. Each participant was evaluated once except for those who had parasitaemia without symptoms, who were followed up by a field assistant for up to 48 hours for the development of symptoms. The period of recruitment was about a month in each season.
Procedures
We conducted the study procedures at a central location in each of the study villages. Field assistants went from house-to-house and recruited the participants and then brought the consenting participants to the central location. The lead investigator screened potential participants for eligibility and the caregivers of eligible participants were required to sign informed consent forms. All recruited subjects were issued with a unique study number, with which they were identified for the entire study. He performed a physical examination for each participant and graded splenomegaly according to Hackett’s criteria 15. The WHO criteria for severe malaria was used 16 to diagnose severe clinical malaria. Using a single use lancet, we collected capillary blood by pricking the index finger of the child’s left hand. A drop of blood was collected each for a thick and thin malaria parasite film for estimation of parasite density and species identification, respectively.
Concomitantly, we did rapid diagnosis of malaria using a drop of blood with CareStart® Malaria HRP2 rapid detection tests (RDTs) (Access Bio, Inc., model G0141), which can detect P. falciparum.
Diagnosis of malaria parasitaemia was done using malaria microscopy. Each day, we transported the samples to the paediatric department laboratory of the Usmanu Danfodiyo University Teaching Hospital and fixing of thick films was done with methanol. Thin films were stained immediately and stored in the lab. We analysed the samples in a completely anonymized manner in pairs of thick and thin films; examining the thin film if we found the thick film positive for malaria. The study numbers were the only identifiers for the thick films, which were kept apart from the thin films. A trained malaria microscopist performed the analysis, under the supervision of a medical parasitologist. We examined at least 10 fields before a slide was declared negative for malaria parasites.
The tail segment of the thin films was viewed by the lead investigator to identify the species of malaria parasite, using the typical description of parasite species, having been trained on parasite identification 17.
Quality control of the diagnosis of the parasitaemia was provided by a trained medical microbiologist re-examining 10% of the slides selected at random. A discrepancy of 10% or more would have necessitated reanalysis of all the thick films and the thin films subsequently. The discrepancy was 3% (kappa score of 0.71) and as such, this was not necessary.
Study participants were determined to have clinical malaria, by the presence of at least one symptom of malaria and a positive RDT or thick blood film. These were treated by the study paediatrician at home with Artemether-Lumefantrine. Children were dosed according to standard dosing 18 but only the first dose was directly observed. Those with severe malaria were determined using the WHO criteria for severe malaria. These children were treated with an initial intramuscular dose of artesunate dosed according to the age 19 and referred immediately to the nearby tertiary hospital (UDUTH).
Statistical analysis
We analysed the data using SPSS version 22. We determined the prevalence of malaria by parasitaemia and RDT by determining proportions no tested positive by each method/ no tested. We used descriptive statistics to determine averages and proportions. Participants with missing data were excluded from the analysis. We carried out sub-group analysis for age, gender and season and used kappa analysis to control the quality of malaria diagnosis.
Results
Participants included
We screened a total of 1136 participants for inclusion in the study after they consented to participation in the study. We excluded 109 because they had been treated with antimalarials in the two weeks prior to enrolment and excluded 10 from the analysis due to incomplete data. We included 1017 participants in the analysis ( Figure 1) 20.
Figure 1. Flow chart for inclusion in analysis for clinical malaria.
The age-sex distribution showed that all ages were equally represented in the study, as shown in Table 1.
Table 1. Age and gender distribution of the subjects included in the study.
| Age
(completed years) |
n | Gender | |
|---|---|---|---|
| Male, n (%) | Female, n (%) | ||
| 2 | 123 | 60 (5.9) | 63 (6.2) |
| 3 | 117 | 63 (6.2) | 54 (5.3) |
| 4 | 110 | 54 (5.3) | 56 (5.5) |
| 5 | 107 | 52 (5.1) | 55 (5.4) |
| 6 | 111 | 62 (6.1) | 49 (4.8) |
| 7 | 111 | 73 (7.2) | 38 (3.7) |
| 8 | 110 | 50 (4.9) | 60 (5.9) |
| 9 | 113 | 54 (5.3) | 59 (5.8) |
| 10 | 115 | 57 (5.6) | 58 (5.7) |
| Total | 1017 | 525 (51.6) | 492 (48.4) |
Prevalence of malaria parasitaemia
We found an overall prevalence of malaria for the study of 34.8% using microscopy and 33.8% using RDT as shown in Table 2. There was an agreement between the two diagnostic methods, as shown by the kappa statistic (p <0.001).
Table 2. Prevalence of malaria parasitaemia among children aged 2-10 years using microscopy and rapid detection test (RDT).
| Test result | Thick film | |||
|---|---|---|---|---|
| Positive | Negative | Total (%) | ||
| RDT | Positive | 295 | 49 | 344 (33.8) |
| Negative | 59 | 614 | 673 (66.2) | |
| Total (%) | 354 (34.8) | 663 (65.2) | 1017 (100.0) | |
Kappa agreement κ = 0.764; p <0.001.
Age-specific prevalence rate of malaria parasitaemia
We saw the highest age-specific prevalence among participants aged two years, with the lowest among ten-year olds. Children aged three years of age at the time of the study had the highest frequency of uncomplicated clinical malaria (42.7%), while the highest frequency of severe complicated malaria was seen among 2-year-olds (9.8%). Children aged 10 years, had the lowest proportion of infected children showing complicated or uncomplicated clinical disease (66.7%) Table 3 also shows a significant association between the age of the participants and prevalence of malaria parasitaemia (p= 0.000).
Table 3. Age-specific prevalence of malaria parasitaemia and clinical malaria.
| Age
(completed years) |
n | Malaria
parasitaemia |
Uncomplicated
Clinical Malaria |
Severe
Malaria |
Proportion of infected
children with clinical disease |
|
|---|---|---|---|---|---|---|
| Positive
Freq (%) |
Negative
Freq (%) |
Positive Freq
(%) |
Positive Freq (%) | % | ||
| 2 | 123 | 62 (50.4) | 61 (49.6) | 46 (37.4) | 12 (9.8) | 93.5 |
| 3 | 117 | 57 (48.7) | 60 (51.3) | 50 (42.7) | 4 (3.4) | 94.7 |
| 4 | 110 | 37 (33.6) | 68 (66.4) | 30 (27.3) | 2 (1.8) | 86.5 |
| 5 | 107 | 39 (36.4) | 68 (63.6) | 30 28.0) | 4 (3.7) | 87.2 |
| 6 | 111 | 38 (34.2) | 73 (65.8) | 31 (27.9) | 0 | 81.6 |
| 7 | 111 | 32 (28.8) | 79 (71.2) | 24 (21.6) | 1 (0.9) | 78.1 |
| 8 | 110 | 30 (27.3) | 80 (72.7) | 25 (22.7) | 1 (0.9) | 86.7 |
| 9 | 113 | 35 (31.0) | 78 (69.0) | 27 (23.9) | 2 (1.8) | 82.9 |
| 10 | 115 | 24 (20.9) | 91 (79.1) | 16 (13.9) | 0 | 66.7 |
| Total | 1017 | 354 (34.8) | 663 (65.2) | 279 (27.4) | 26 | 86.2 |
χ 2 = 38.453; df = 8; p<0.01.
Parasite species causing malaria
Of the 354 children included in the study with malaria parasitaemia by microscopy, 279 participants were found to have clinical malaria across the seasons and all of them had P. falciparum malaria, irrespective of the season and nature of their clinical presentation. The relative proportions of the results of malaria infection are depicted in Figure 2. The figure basically shows the proportion of children with any malaria parasiatemia (34.8%) of which, 92% had fever. The most common presenting feature among these was fever (92%), followed by vomiting (38%), refusal to feed/poor appetite (32%) and body weakness (25%).
Figure 2. Distribution of nature of malaria infections.
Aside the uncomplicated clinical cases of malaria, 9.6% had complicated malaria, as indicated by the WHO criteria for severity 21. The number of severe malaria cases was significantly lower in the dry season than the rainy season, as shown in Table 4. Different participants had various combinations of the criteria for severity, although the common criteria were hyperpyrexia, prostration and persistent vomiting.
Table 4. Prevalence of severe malaria across seasons.
| Season | N | Severe malaria
Freq (%) |
Other cases
Freq (%) |
|---|---|---|---|
| Rainy season | 511 | 24 (4.7) | 487 (95.3) |
| Dry season | 506 | 2 (0.4) | 504 (99.6) |
| Total | 1017 | 26 (2.6) | 991 (97.4) |
χ 2 = 18.883; df = 1; p = 0.000.
Comparison of prevalence between the seasons
The prevalence of malaria parasitaemia during the rainy season was significantly higher than the dry season, with prevalence rates of 49.3% and 20.2%, respectively, all due to P. falciparum.
Parasite density across the seasons
The mean parasite density was much higher during the rainy season (1006.13) than during the dry season (405.45). The details are shown in Table 5.
Table 5. Parasite density across the seasons (parasites/µL).
| Season | Mean | SD | Minimum | Maximum | Interquartile
range |
|---|---|---|---|---|---|
| Rainy | 1006.13 | 495.8 | 16 | 284000 | 840 |
| Dry | 405.45 | 209.48 | 16 | 204000 | 640 |
| Overall | 833.1 | 443.8 | 16 | 284000 | 1064 |
Discussion
The prevalence of malaria in this study, when compared with serial MIS’s performed in 2010 14 and 2015 22 shows a progressive reduction; from 48.1% to 37.1% for north-western Nigeria, and a prevalence of 46.6% for Sokoto in 2015 compared with 34.8% for our study. Prevalence in the MIS’s was measured among children aged six to 59 months and is probably higher than for the children included in this study because including the children from 6–10 years is likely to reduce the overall prevalence, as is excluding those aged six months to two years, who generally have a higher prevalence rate 23. This suggests that the prevalence and intensity of malaria transmission has declined over time, particularly when it is juxtaposed against the rate of uptake of Long-Lasting Insecticide Treated Nets (LLINS) 14, 22.
Although there were studies performed in the past in Sokoto, they are limited in comparison to the present study by virtue of having been conducted in a different age group, or hospital in lieu of community setting and the seasons in which these studies were conducted. The prevalence of 34.8% found here was higher than the 27.9% found by Abdullahi et al. 13 in Sokoto; however, samples in the previous study were collected from patients visiting two hospitals within the metropolis and was thus not community-based. Furthermore, all ages from 0 to 65 years were included in the study, which is likely to further dilute the findings and give a falsely low prevalence because the incidence of malaria is generally lower among adolescents and adults, as indicated in the study. Further lending credence to the claim of a reduction in the prevalence of malaria, likely owing to better access to malaria prevention and increasing urbanisation; both of which cause a decline in malaria parasite rates generally 24.
The prevalence found in this study is also lower in comparison to the 45.4% prevalence rate found in a study by Jiya et al. 25, conducted in Sokoto between 2007 and 2009. Additionally, it was lower than the prevalence of 49.6% found among children under the age of five years in the same study. Considering both age-specific prevalence rates, there is a reduction in prevalence, although being a hospital-based study, the prevalence for the former study is likely to be higher than the current. It is, however slightly, higher than the projected national average of 29% for 2015, with wide inter-regional differences 26. The Nigerian MIS of 2015 found a higher prevalence of 46.6% than this study, although the age of included participants ranged from six to 59 months, which will limit the comparability of results from this study due to the different age ranges of participants 22. This decline in the prevalence should reflect in the distribution of the parasites as theorised by Lucas and Gilles 27 who propounded a theory of disappearance of species as control measures improve until complete elimination is achieved.
The prevalence by age in this study roughly indicated a progressive decline with age. The highest age-specific prevalence was among two-year-olds (50.4%), with a statistically significant difference among the age groups. This finding is in conformity with the steady-state assumption and is like findings in previous studies that showed higher prevalence among younger age-groups. The prevalence of uncomplicated clinical malaria was highest among three-year-olds and two-year-olds, and lowest among ten-ten-year olds, also in keeping with the steady-state-theory. Considered altogether, the under-fives constituted the largest proportion of uncomplicated and complicated malaria cases, and this is to be expected, considering that they are the least immune to malaria.
With respect to the parasite species causing uncomplicated malaria, all parasitaemia in this study was found to be due to P. falciparum. This is similar to findings in recent studies in Adamawa 28 and Cross River states 10 in 2011 and 2013, respectively. Another study from Ihiala, in Anambra state of south-eastern Nigeria, found P. falciparum mono-parasitaemia even though this study considered all types of malaria, both severe and uncomplicated 29. This is, however, unlikely to affect the findings, as most cases of severe malaria in this area are due to P. falciparum 29 . An earlier report from Sokoto between 2005 and 2006, carried out at Usmanu Danfodiyo University Teaching Hospital by Jiya and Sani 25, 30 likewise did not find any Plasmodium species apart from P. falciparum, although they only considered cases of severe malaria, which are unlikely to be due to a different species of Plasmodium within Nigeria. Meanwhile, only three cases out of 582 (0.01%) were positive for P.malariae in another study by Nwaorgu and Orajaka 31 in Awka, south-eastern Nigeria. A major limitation of the studies described is the population selected for hospital-based studies, which was mostly children with severe, complicated malaria, for which there is likely to be monoparasitaemia. The community-based studies are expected to truly reflect the distribution of parasite species because in the absence of radical-cure treatment with primaquine as is the case in Nigeria, P. malariae and P. ovale infections are likely to persist in the population. Other studies in the past had not explicitly described the process of identifying other parasite species and that could be a weakness in those studies. However, in our study which was community-based, we pound P. falciparum monoparasitaemia in spite of methodologically searching for other Plasmodium species. This leads us to believe that this is a true P. falciparum monoparasitaemia, contrary to expectation. The finding of P. falciparum mono-parasitaemia supports the likelihood that P. falciparum is the dominant species of Plasmodium in Sub-Saharan Africa, showing at tendency to exclude other forms of parasitaemia, as expounded by Lucas and Gilles 27 in 1998 with time and sustained malaria control activities.
Other studies have expectedly shown the presence of other forms of parasitaemia, notably with P. malariae either as mono-infection or coinfection with P. falciparum. In Abia and Plateau states (2010), P. malariae accounted for 32.0% and 1.4% of malaria infections, respectively 7 in malariometric surveys In another community-based study in north-central Nigeria, 6.1% of examined participants had P. malariae infection 32 and as high as 41% and 4%, respectively, had P. malariae and P. ovale infections in a historical study in Garki, Abuja (1968) 33. Outside Nigeria, there has also been a documented shift towards mono-parasitaemia with P. falciparum, and this has been documented in the Horn of Africa 34 and Benin in West Africa 35. Some authors have suggested it be an evidence of failing control measures but this is at variance with data from this study, which shows a reduction in prevalence from previous data, including a reduction in the number of severe cases of malaria, which were very few in this study both in the rainy and dry seasons, reflecting better malaria control than seen in previous studies.
Severe malaria was seen in 26 of the 1017 participants analysed in this study, with an overall prevalence of 2.6%. It was higher during the rainy than the dry season, probably due to higher prevalence of the disease and higher parasitaemia, as earlier discussed. This is lower than expected from other hospital-based studies for which children presenting to the hospital are more likely to be ill than those found in a community-based survey such as this. In one such study in Ilorin by Olanrewaju and Johnson 27 found that a third of all children admitted with malaria had a severe form of malaria.
Uncomplicated, clinical malaria was seen in 279 of the children in the study (27.4%), which is relatively high, considering that it was community based. The proportion of tested children with malaria parasitaemia who had uncomplicated malaria was also high overall (86.2%) and higher in the rainy than the dry season. The role of Seasonal Malaria Chemoprophylaxis (SMC) would thus be relevant in reducing this percentage of positives with clinical malaria 36.
Our study is limited by the point estimation of malaria prevalence, for which a time-series would have been preferred to document consistently the changes over time. Also, the use of RDT kits, could have been complimentary to microscopy for the diagnosis of malaria species if we used a kit with the ability to detect other parasite species.
Conclusions
We found that the area had an intermediate endemicity of malaria transmission. Despite this, there was P. falciparum monoparasitaemia. This suggests a disappearance of other parasite species, either due to faltering control of P. falciparum leading to dominance by these species or more efficient control of other species. However, the trend of overall endemicity suggests the latter explanation, implying a need to intensify measures to control P. falciparum, considering its strategic role in causing clinically severe malaria in SSA.
Data availability
Underlying data
Figshare: complete data.xlsx. https://doi.org/10.6084/m9.figshare.11590542.v1 20.
Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).
Acknowledgements
With their permission, we wish to acknowledge Abdurrahman I and Yakubu B for assisting in the laboratory analysis and Jap Van Hellmond for providing guidance with species identification.
Funding Statement
The study was funded by a dissertation grant awarded to UNN by Usmanu Danfodiyo University Teaching Hospital, Sokoto, Nigeria.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
[version 2; peer review: 1 approved
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