You are viewing the site in preview mode

Skip to main content
Download PDF
Download ePub

Non-random distribution of Plasmodium Species infections and associated clinical features in children in the lake Victoria region, Kenya, 2012–2018

Tropical Medicine and Health volume 52, Article number: 52 (2024) Cite this article

Abstract

Background

While Plasmodium falciparum (Pf) stands out as the most lethal malaria parasite species in humans, the impact of other species should not be dismissed. Moreover, there is a notable lack of understanding of mixed-species infections and their clinical implications.

Methods

We conducted eight school-based cross-sectional malariometric surveys in the Lake Victoria region of western Kenya between January–February 2012 and September–October 2018. In each survey, a minimum of 100 children aged 3 to 15 years were randomly chosen from a school in Ungoye village on the mainland and as well as from each school selected in every catchment area on Mfangano island. Plasmodium infection was determined by microscopy and nested polymerase chain reaction (PCR). The multiple-kind lottery (MKL) model calculated the expected distribution of Plasmodium infections in the population and compared it to observed values using a chi-squared test (χ2).

Results

The Plasmodium prevalence was 25.9% (2521/9724) by microscopy and 51.1% (4969/9724) by PCR. Among all infections detected by PCR, Pf, P. malariae (Pm), and P. ovale (Po) mono-infections were 58.6%, 3.1%, and 1.8%, respectively. Pf/Pm, Pf/Po, Pm/Po, and Pf/Pm/Po co-infections were 23.5%, 4.3%, 0.1%, and 8.6%, respectively. MKL modelling revealed non-random distributions, with frequencies of Pf/Pm and Pf/Pm/Po co-infections being significantly higher than expected (χ2 = 3385.60, p < 0.001). Pf co-infections with Pm and Po were associated with a decreased risk of fever (aOR 0.64, 95% CI 0.46–0.83; p = 0.01) and increased risks of splenomegaly (aOR 12.79, 95% CI 9.69–16.9; p < 0.001) and anaemia (aOR 2.57, 95% CI 2.09–3.15; p < 0.001), compared to single-species infections.

Conclusion

This study sheds light on the potential interaction between Pf and Pm and/or Po. Given the clinical significance of mixed-species infections, improved diagnostics, and case management of Pm and Po are urgently needed.

Introduction

Malaria remains a significant global public health concern, especially in sub-Saharan Africa. In 2022, there were estimated 249 million malaria cases in 85 endemic countries, resulting in 608,000 deaths according to the World Health Organization (WHO) [1]. Alarmingly, children under the age of five accounted for 76% of these malaria-related fatalities [1]. Efforts to control malaria in sub-Saharan Africa have primarily focused on Plasmodium falciparum (Pf), the most lethal human Plasmodium species. However, P. malariae (Pm) and P. ovale (Po) are endemic in many parts of sub-Saharan Africa and mixed-species infections are common, with nearly all possible combinations observed within human populations [2,3,4].

Interactions between co-occurring Plasmodium species can influence infection dynamics, species prevalence, and distribution due to resource competition, varying levels of virulence, and the host's immune response to each species [5,6,7,8]. The consequences of co-infection on infection virulence have been well documented in rodent malaria, as controlled experiments with human malaria are not feasible. Tang et al. [8] found that co-infections of P. yoelii with either P. vinckei or P. chabaudi significantly increased infection virulence, resulting in 100% mortality in mixed species infections. In contrast, single infections of P. yoelii and P. vinckei caused no mortality, and P. chabaudi alone caused 40% mortality. Previous studies have linked these interspecies interactions to either increased or reduced likelihood of severe malaria development in children, depending on the parasite species involved. For instance, a prospective cohort study from Papua New Guinea (PNG) found that P. vivax and mixed infections were associated with severe malaria in children [9]. In contrast, coinfections with Pm were found to reduce the severity of fevers in children in West Africa [10]. Mixed-species infections remain a persistent challenge to malaria elimination efforts due to their variability in case management and transmission prevention. Natural interactions among Plasmodium species in humans also appear to differ by geography, which can result from differences in climate and genetic characteristics in host and vector populations [11, 12].

With a surface area of 69,485 km2 and an altitude of 1,135 m above sea level, Lake Victoria is the world's second-largest freshwater lake. In Homa Bay County, Kenya, the Lake Victoria basin encompasses two populous islands, Rusinga and Mfangano, as well as several smaller inhabited islands (Fig. 1). Due to the year-round availability of suitable breeding sites, these islands and lakeside villages have a high density of Anopheles vectors [13]. Our earlier study in the region revealed that most PCR-detected Plasmodium infections were asymptomatic (91.8%) and submicroscopic (50.3%). We reported a prevalence of 13.2% for non-falciparum (P. malariae and P. ovale) infections and 11.3% for mixed Plasmodium infections by PCR. Additionally, the lakeshore community of Ungoye and Mfangano island showed a higher prevalence of non-falciparum and mixed Plasmodium infections than smaller islands [14]. Another study conducted among health facilities in six different regions of Kenya found that non-falciparum and mixed infections comprised 27.5% and 25.8%, respectively, of symptomatic cases [15]; however, they did not reflect the community prevalence. Apart from the difference in a wide range of ecological factors, such as climate and vector-human interactions, these differences suggest distinct geographical niches for specific species. Differential species burden patterns observed across malaria-endemic areas highlight the need for improved diagnostic tools and a better understanding of the epidemiology of mixed Plasmodium and non-falciparum malaria and their clinical implications [12, 16].

Fig. 1
figure 1

The Lake Victoria basin of Homabay County in western Kenya where the malaria cross-sectional surveys were conducted

Full size image

To date, mixed Plasmodium infections have frequently been overlooked or underestimated when microscopy is used. While molecular diagnostic methods have revealed that non-falciparum single and mixed infections are more common throughout sub-Saharan Africa and other malaria-endemic regions of the world, their epidemiology remains far less studied [17,18,19,20]. The clinical implications of these non-falciparum species, which may differ from those of Pf, are poorly understood within endemic human populations. The main concern of missed mixed infections is that inadequate treatment or disease management could result in debilitating infections and their associated economic and social consequences after Pf is eliminated.

In this study, we conducted repeated cross-sectional surveys between 2012 and 2018 in the Lake Victoria region of Western Kenya. Our goal was to determine the distribution of mixed malaria infections using molecular diagnostic methods and identify clinically relevant features of these infections. We employed a multiple-kind lottery model (MKL) to investigate whether the occurrence of different Plasmodium species is independent of species-to-species interactions and to evaluate changes in the distribution of various parasite species combinations in the study population for six years. We further analysed the effect of single-species and mixed infections with Pf, Pm, and Po on the clinical features of malaria recorded on the day of enrolment using logistic regression models.

Methods

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Kenyatta National Hospital/University of Nairobi-Ethics and Research Committee in Kenya (No. P7/1/2012), the Mount Kenya University Independent Ethics and Research Committee (MKU-IERC) and the Ethics Committee at Osaka Metropolitan University (approval number 3206). Local interpreters explained the purposes and procedures of the study to the survey subjects, and written informed consent was obtained from each adult participant during study registration. For children, written informed consent was obtained from their parents or legal guardians.

Study sites

Ungoye (19.3 km2) is a village on Lake Victoria's shore in Homa Bay County, Kenya. According to the 2019 Kenya Population and Housing Census [21], it had a population of about 5000. Mfangano Island (66 km2) is approximately 12 km northwest of Ungoye and has a population of 25000 (Fig. 1). This region typically experiences a short rainy season between November and December and a long rainy season between March and June. Peak malaria transmission occurs 4–8 weeks after the rainy season and is often associated with up to eight-fold increases in malaria vector abundance [22]. The relative abundance of malaria vector species and suitable larval habitats has been linked with the high and heterogeneous malaria prevalence between neighbouring Islands and the mainland in Lake Victoria [14].

Study design

Eight cross-sectional school-based malariometric surveys were conducted between January–February 2012 and September–October 2018. In Ungoye the same primary school was sampled throughout the study period. On Mfangano, catchment areas were defined by geographic features (coastal lowland vs. interior mountains) and proximity to population centres and major villages, and corresponded approximately to the east coast, highland, and west coast as described by Idris et al. [14]. At least one public primary school within each catchment area, totalling four to six schools per survey were sampled to adequately cover the entirety of the island. We obtained lists of school children from selected schools and systematically selected a minimum of 100 children at random to participate in the study. For six years, the surveys were conducted about two months after the rainy seasons, specifically in October-December and February–March, to coincide with the periods with the highest malaria transmission.

Field methods and laboratory procedures

Before sample collection, appropriate collection and processing protocols were designed to ensure samples were collected and identified correctly. The sex and age of each participant were recorded at enrolment. Axillary temperature was determined using a digital thermometer (Terumo, Tokyo, Japan). Participants aged 12 years and under were examined for clinically palpable spleen according to Hackett's method [23] by author AK.

Finger-prick blood samples were collected from each participant for the determination of haemoglobin level by HemoCue Hb 201 + analyser (HemoCue, Ängelholm, Sweden) and Plasmodium infections by rapid diagnostic test (RDT), light microscopy, and PCR. P. falciparum infections were diagnosed on-site using the Paracheck Pf RDT (Orchid Biomedical System, Goa, India), and RDT-positive participants were given artemether-lumefantrine treatments with instructions according to the Ministry of Health's case management guidelines for uncomplicated malaria. Thick and thin blood smears were made on a glass slide. The thin blood smear was fixed with methanol, and both smears were stained with 3% Giemsa solution for 30 min. Samples were examined by two independent experienced microscopists and considered negative if no parasites were observed after examination of 100 fields under 1000X magnification. A third experienced microscopist, who was blinded to the results from the initial two examinations, resolved any discrepancies. Two blood spots (70 μl each) were blotted on Whatman 31ET Chr filter paper (Cytiva Life Sciences, Tokyo, Japan) using heparinised microhaematocrit capillary tubes (Thermo Fisher Scientific, USA). Blood spots were allowed to dry at ambient temperature, packed in individual zippered plastic bags containing silica gel desiccant and stored at -20 °C. The QIAamp Blood Mini Kit (QIAGEN, Germantown, USA) was used to extract DNA from a quartered blood spot (17.5 μl) according to the manufacturer's instructions. A nested PCR procedure described by Isozumi et al. [24], which can differentiate the four primary human malaria species except P. knowlesi, was used to detect Plasmodium infection. Negative controls and positive controls (purified Plasmodium DNA from BEI Resources, Manassas, Virginia, USA) were included in both primary and secondary PCRs.

Variable definitions

A Plasmodium infection was defined by positive PCR of one or more Plasmodium species. Samples that were positive by microscopy but negative by PCR were treated as negative in any analysis. Fever was defined as an axillary temperature ≥ 37.5 °C, and infections without fever were considered asymptomatic. The age groups were defined as below 5 years, 5–10 years, and 11–15 years, as defined before in our setting [14]. Non-anaemia, mild and moderate anaemia, and severe anaemia for children in each age category were defined according to the World Health Organization standard [25]. Severe malarial anaemia was defined as Hb ≤ 5 g/dL in the presence of any malaria parasite by microscopy and/or PCR [26]. Splenomegaly was defined using Hackett's spleen size classification in a score of 0–5, reflecting the degree of splenic enlargement [23].

Data management and statistical methods

All analyses were done using Stata/SE 16.1 (StataCorp, Texas, USA) and R version 4.2.2 (The R Foundation for Statistical Computing, Vienna, Austria). Descriptive statistics were calculated for each study site yearly. Means were compared between study sites using Student's t-test or Mann–Whitney rank test, while proportions were compared using Pearson's Chi-square tests or Fisher exact tests. The average enlarged spleen (AES) index was calculated as the sum of the number of children in each spleen size class multiplied by the class number (0–5), divided by the total number of palpable spleen. The MKL model [27] was used to tabulate the species' expected numbers and all the combinations in each population (more detail about the model provided in the supplementary materials). The Chi-square tests for heterogeneity were used to compare observed with expected numbers of infections. Univariable and multivariable mixed effects logistic regression models generated adjusted odds ratios (aOR) and 95% confidence intervals (CI) adjusting for age, sex, and survey year to assess the association between single and mixed Plasmodium infection status, fever, splenomegaly (clinically palpable spleen), and anaemia, with school set as the random effect. The analysis was performed using the glmer function in the lme4 R package. A multinomial logistic regression model was used to evaluate the relative risk ratio of Pf mono-infections jointly, Pf mixed-species infections, and non-falciparum infections over time while adjusting for the above-specified covariates.

Results

Study participants

We analysed data from 9724 school children aged between 3 and 15 years, with 6286 children from Mfangano and 3438 from Ungoye, throughout the study period (Table 1). Among these participants, slightly more than half were females (50.9%), and the average age was 8.2 years. Most participants belonged to age categories of either 5–10 or 11–15-year (80.4%; 95% Confidence Interval CI 78.5–82.4).

Table 1 Participants characteristics by study site
Full size table

Plasmodium species-specific prevalence and clinical outcomes

The overall prevalence of Plasmodium infections in Ungoye was significantly (p < 0.001) higher than that in Mfangano, and this difference was observed throughout the study period by both PCR and microscopy (Supplementary Fig. 1).

In both Ungoye and Mfangano, the species-specific prevalence of Pf, Pm, and Po remained consistent between 2012 and 2018 (Fig. 2). Species-specific prevalence of all three species as determined by PCR and microscopy was dependent on age (p < 0.001), with the lowest overall prevalence observed in children under the age of 5 (Supplementary Fig. 2). By PCR, the 11–15 age group (n = 3106) had the highest Pf- (53.1%; 95% CI 50.8–56.1) and Pm-specific (18.9%; 95% CI 16.2–19.8) prevalence, while the 5–10 age group (n = 4715) had the highest Po-specific prevalence (8.4%; 95% CI 6.5–9.6,).

Fig. 2
figure 2

Yearly (2012–2018) Plasmodium species-specific prevalence detected by polymerase chain reaction. A Ungoye. B Mfangano island. Error bars represent 95% confidence intervals. No surveys were conducted in 2016. Pf Plasmodium falciparum, Pm Plasmodium malariae, Po Plasmodium ovale

Full size image

Of all participants, 1313 (13.6%; 95% CI 12.8–14.3) were febrile, and 2618 (27.3%; 95% CI 25.7–28.8) had a haemoglobin measurement below 11 g/dl. Of all the children with anaemia, 1159 (12.1%; 95% CI 11.4–12.7), 1333 (13.2%; 95% CI 13.2–14.6), and 126 (1.1%; 95% CI 1.1–1.6) had mild, moderate, and severe anaemia, respectively, based on the WHO standard. Among those screened for splenomegaly (aged 3–12 years), 3188 (45.5%; 95% CI 44.3–46.7) were found to have an enlarged spleen, with an AES index of 1.73. The prevalence of enlarged spleen was significantly (p < 0.001) higher in Ungoye (59.2%; 95% CI 57.3–61.1, AES = 1.78) compared to Mfangano (37.3%; 95% CI 35.9–38.8, AES = 1.70) (Table 1).

Plasmodium species infections

Out of the total 9724 children included in the study, PCR detected 4969 Plasmodium infections (51.1%; 95% CI 50.1–52.1). The majority, 2910 (58.6%; 95% CI 57.2–59.9), were identified as Pf mono-infections, 153 (3.0%; 95% CI 2.6–3.6) as Pm mono-infections, and 87 (1.7%; 95% CI 1.4–2.1) as Po mono-infections. Furthermore, there were 1170 cases (23.5%; 95% CI 22.4–24.7) of Pf/Pm, 216 (4.3%; 95% CI 3.8–4.9) Pf/Po, 6 (0.1%; 95% CI 0.05–0.3) Pm/Po, and 427 (8.6%; 95% CI 7.8–9.4) Pf/Pm/Po mixed infections (Fig. 3). A similar trend in proportion was observed when data was analysed across the sites. However, the proportion of mixed infections involving Pf (Pf/Pm and Pf/Pm/Po) was significantly higher in Ungoye compared to Mfangano island (Pf/Pm: 29.9%; 95% CI 28.0–31.8 vs 18.2%; 95% CI 16.8–19.7, p = 0.002, and Pf/Pm/Po: 12.6%; 95% CI 11.3–14.0 vs 5.3%; 95% CI 4.5–6.2, p < 0.001, Supplementary Fig. 3).

Fig. 3
figure 3

Proportion of Plasmodium mono and mixed-species infections among the positive cases by polymerase chain reaction (n = 4969). The error bars represent a 95% confidence interval (CI). Pf Plasmodium falciparum, Pm Plasmodium malariae, Po Plasmodium ovale

Full size image

Distribution of mixed-species infections

The frequencies of Plasmodium assemblages deviated significantly from the random pattern predicted by the MKL model for both PCR (χ2 = 3385.60; df = 7; p < 0.001) and microscopy (χ2 = 459.73; df = 7; p < 0.001) (Table 2). We observed higher-than-expected numbers of Pf/Pm and Pf/Pm/Po mixed infections, while the numbers of Pf/Po and Pm/Po mixed infections and single-species (Pf, Pm and Po) infections were lower than expected (Table 2).

Table 2 Observed and expected frequencies of Plasmodium species infections by PCR and Microscopy
Full size table

Next, we analysed whether the distribution pattern of Plasmodium infections was influenced by age or study site. We categorised the children into three age groups: below 5 years (n = 1903), 5–10 years (n = 4715), and 11–15 years (n = 3106). By PCR, significant (all p < 0.001) deviations from a random distribution pattern were observed for all age groups (Table 3). By study site, significant deviations were observed in both Ungoye (χ2 = 1621.17; df = 7; p < 0.001) and Mfangano (χ2 = 1211.89; df = 7; p < 0.001) (Table 4).

Table 3 Observed and expected frequencies of Plasmodium species infections by age group-PCR analysis
Full size table
Table 4 Observed and expected frequencies of Plasmodium species infections by study site-PCR analysis
Full size table

Association with clinical measures of malaria

After adjusting for age, sex, study site, and year of survey in logistic regression models, Pf/Pm (aOR = 0.68, 95% CI 0.51–0.87, p = 0.03) and Pf/Pm/Po (aOR = 0.64, 95% CI 0.46–0.83, p = 0.01) mixed infections were significantly associated with reduced risks of fever, while Pf mono-infections were significantly (aOR = 1.59, 95% CI (1.39–1.82, p < 0.01) associated with an increased risk of fever. Pf mono-infections and mixed-infections with Pm and/or Po were significantly associated with anaemia and palpable spleen when compared to infections caused by a single species, as shown in Fig. 4.

Fig. 4
figure 4

Clinical features association with Plasmodium single and mixed species infection. A Clinical fever at presentation defined as an axillary temperature ≥ 37.5 °C, B Moderate or severe malarial anaemia defined according to WHO standard, C Enlarged spleen according to Hackett's method. The odds ratios are adjusted for age, sex, school, and year of the survey. The error bars indicate the 95% confidence interval. Pf Plasmodium falciparum, Pm Plasmodium malariae, Po Plasmodium ovale. Significant odds ratios (p > 0.001), are indicated in red

Full size image

Risk for mixed Plasmodium species infections

We investigated the risk factors associated with infections caused by single and multiple species of Plasmodium in children. Both Pf and Pf/Pm or Pf/Pm/Po showed significant association with age group, the use of insecticide-treated nets (ITNs), and the location of the study. Notably, the likelihood of contracting Pf mixed infections, specifically Pf/Pm and Pf/Pm/Po, was approximately four and six times higher, respectively (aOR = 4.15; 95% CI 3.63–4.74 and aOR = 6.03; 95% CI 4.88–7.45, p < 0.001) in children from Ungoye compared to those from Mfangano (Table 5).

Table 5 Risk Factors for single and mixed Plasmodium infections in children
Full size table

The multinomial logistic model was also used to estimate the relative risk ratio of all the single and mixed Plasmodium infections compared to being uninfected over time. The model-predicted adjusted probability and relative risk ratio of mixed infections involving Pf and Pm with and without Po (Pf/Pm and Pf/Pm/Po) and Po mono-infection increased significantly (p < 0.001), while the probability of Pf mono-infection decreased significantly (p < 0.001). (Supplementary Table 1, Supplementary Fig. 4).

Discussion

Detailed analysis of results from a series of cross-sectional school surveys in the Lake Victoria basin of Kenya showed that Plasmodium species were non-randomly distributed among infections. Higher-than-expected numbers of Pf/Pm and Pf/Pm/Po co-infections were observed when the infections were diagnosed by microscopy or PCR, and when the population was stratified by age groups and geographical settings Interestingly, Pf/Pm and Pf/Pm/Po co-infections were associated with a reduced risk of fever but an increased risk of splenomegaly and anemia compared to single-species infections.

Our findings of non-random association of Plasmodium species are consistent with previous studies in sub-Saharan Africa [28,29,30] but contrast with those in PNG [31, 32]. These variations could be attributed to the different sets of sympatric species included [11]. Non-random distribution occurs when one parasite species either excludes another or when they are transmitted together, suggesting an effective interspecific interaction [27]. Malaria parasites are known to engage in mutual suppression in infected hosts, however, which species suppress the other is not well understood [11, 33]. The most straightforward explanations are through competition of nutrients and red blood cells (RBCs) [33, 34]. Whereas Pm and Po infect only mature and young (reticulocytes) RBCs respectively, Pf prefers young RBCs but is capable of invading all RBC age classes [35]. Hence, high Pf parasite density may reduce the availability of RBCs for invasion by other species [33]. McQueen and McKenzie [36] found that competition for RBCs generally increased P. vivax parasitemia in mixed-species malaria infections, although this effect varied based on the species' relative reproduction rates and the timing of inoculation.

Activation of nonspecific host-defence mechanisms could also restrict the proliferation of the accompanying parasite, especially during the rapid exponential growth phase [37]. Clinical studies have shown the existence of cross-species immunity in human malaria species [38, 39]. However as reported by Bruce et al. [7], when the majority population (in our case Pf which constitutes the majority of the infections in children) is cleared by species-specific immunity, total density will drop below the threshold that can trigger suppression (density-dependent regulation). In these circumstances, the minority population (Pm and Po) could expand because there is no competition [7]. This could explain why mixed Plasmodium infections (double infection of Pf and Pm, or triple infection of Pf, Pm and Po) are common in our study population, which primarily comprise asymptomatic and sub-microscopic infections. With respect to malaria control and elimination, our findings suggest that if species-specific vaccines or treatments successfully prevent or reduce Pf infections in highly endemic areas, the absence of constraints imposed by density-dependent regulation could allow non-falciparum species like Pm and Po to proliferate. Consequently, misdiagnosis and suboptimal drug treatment (e.g. no primaquine or tafenoquine radical treatment for Po) can allow the latent species to persist with serious clinical repercussions [33].

Additionally, the extent to which persistent parasitaemia in asymptomatic mixed species infections is a result of density-dependent regulation or immune response to numerous antigenic variants, along with its clinical implications, remains poorly understood [40]. Our findings indicate that children with mixed infections comprising double infections of Pf and Pm, or triple infections of Pf, Pm and Po had lower odds of having fever compared to those with single Pf infections at enrolment (Fig. 4A). Black et al. [10] suggested that Pm infections ameliorate the fevers of subsequent Pf superinfections in West African children due to constant exposure to parasites by frequent re-infection or long-term survival of parasites at low parasitaemia. Two previous studies conducted in Malawi and Tanzania similarly demonstrated that children with mixed Plasmodium infections had significantly reduced parasite density compared to children with single Pf but mixed infections were not correlated with fever reduction [41, 42].

However, mixed infections were also associated with unfavourable clinical features, double (Pf/Pm) and triple co-infections (Pf/Pm/Po) were more strongly associated with moderate or severe anaemia compared to children with single Pf infections (Fig. 4B). The contribution of persistent parasitaemia at sub-microscopic levels in mixed infections to the development of anaemia remains uncertain, and there is still controversy about the role of asymptomatic infections in infected children [43]. Nonetheless, it has been proposed that prolonged infections with the slowly replicating Pm and Po lead to continuous destruction of both parasitised and non-parasitised RBCs [44]. We also found an association between co-infections comprising Pf and Pm, both with and without Po and splenomegaly (Fig. 4C), which aligns with a previous study in Uganda [30]. There is conflicting evidence on spleen enlargement in children with mixed infections compared to those with single-species infections [45, 46], but our finding adds more evidence to the clinical relevance of infection with non-falciparum species within mixed-species infections.

We observed that the risk of Pf/Pm and Pf/Pm/Po mixed infections was significantly higher in children from Ungoye compared to those from Mfangano (Table 5). The high malaria prevalence in Ungoye has been linked to unpaved roads and extensive irrigation for farming, which create ample favourable Anopheles larval habitats [13]. Field studies have demonstrated that at least seven Anopheles species can carry more than one human Plasmodium species [47]. For instance, An. gambiae can carry all four major human Plasmodium species simultaneously [48]. Since female anopheline mosquitoes feed on human blood multiple times throughout their lives, areas with high malaria transmission could see both sequential and simultaneous transmission of different Plasmodium species and genotypes within species. Nonetheless, other non-entomological factors such as household structure features, occupation, and individual attractiveness to vector bites may influence the variation in mixed Plasmodium infections in our study area, but they are not fully understood.

The MKL model utilises prevalence data to provide a more realistic approximation of malaria infections in natural settings, as some hosts are infected with more than one parasite species simultaneously while others remain uninfected [27, 32]. However, it is important to acknowledge that this study focused exclusively on the prevalence of infection, not parasitaemia or parasite density. However, since PCR-based diagnosis is sufficiently sensitive to provide a comprehensive assessment of parasites involved in individual infections, it was possible to determine if there was evidence for cross-species interaction (non-random distribution) statistically. Further investigations on parasite density using quantitative molecular tests and other statistical models will be beneficial in providing a full assessment of the species-specific effect on parasite density. The cross-sectional nature of our sample collections also precluded us from examining how each Plasmodium species in mixed-species infections was acquired and whether one species may persist longer than others. Furthermore, the clinical effects of mixed infections could not be monitored longitudinally. School-based surveys are efficient and target the age groups with the highest Plasmodium prevalence in our study area [14], however, it remains unclear whether the pattern of excess Pf/Pm and Pf/Pm/Po infections and their association with negative clinical features are observed in adults who have more robust immunity against Pf. Another limitation of our study is that children from the same school in our study were sampled over time, which means some children might have participated in more than one surveys. Artemether-lumefantrine treatment cleared parasitaemia in RDT-positive cases during the school surveys. However, parasitaemia in sub-microscopic infections, which were detected only by PCR, is persistent with decreasing parasite density over an extended period [49]. Given the high entomological inoculation rates (EIRs) in our study area [50], this persistent parasitaemia is gradually dominated by new infections. In each school survey, we detected most probably new infections, even though some children were repeatedly surveyed. As mentioned above, the results of infections detected by microscopy and those by PCR were not different.

In conclusion, PCR of blood samples from a series of cross-sectional surveys in school children in a region characterized by high and heterogeneous prevalence of malaria [14] has demonstrated that mixed Plasmodium infections are remarkably common and non-randomly distributed. Given the clinical significance of mixed-species infections, improved diagnostics, and case management of Pm and Po are urgently needed.

Data availability

The data used during the analysis is available upon reasonable request from the corresponding author.

References

  1. World Health Organization. World malaria report 2023. Geneva: World Health Organization; 2023.

    Google Scholar 

  2. Roucher C, Rogier C, Sokhna C, Tall A, Trape JF. A 20-year longitudinal study of Plasmodium ovale and Plasmodium malariae prevalence and morbidity in a West African population. PLoS ONE. 2014;9(2): e87169.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Sutherland CJ. Persistent parasitism: the adaptive biology of malariae and ovale malaria. Trends Parasit. 2016;32(10):808–19.

    Article  Google Scholar 

  4. Oguike MC, Betson M, Burke M, Nolder D, Stothard JR, Kleinschmidt I, et al. Plasmodium ovale curtisi and Plasmodium ovale wallikeri circulate simultaneously in African communities. Int J Parasit. 2011;41(6):677–83.

    Article  Google Scholar 

  5. Ramiro RS, Pollitt LC, Mideo N, Reece SE. Facilitation through altered resource availability in a mixed-species rodent malaria infection. Ecol Lett. 2016;19(9):1041–50.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Zimmerman PA, Mehlotra RK, Kasehagen LJ, Kazura JW. Why do we need to know more about mixed Plasmodium species infections in humans? Trends Parasit. 2004;20(9):440–7.

    Article  Google Scholar 

  7. Bruce MC, Donnelly CA, Alpers MP, Galinski MR, Barnwell JW, Walliker D, et al. Cross-species interactions between malaria parasites in humans. Science. 2000;287(5454):845–8.

    Article  CAS  PubMed  Google Scholar 

  8. Tang J, Templeton TJ, Cao J, Culleton R. The consequences of mixed-species malaria parasite co-infections in mice and mosquitoes for disease severity, parasite fitness, and transmission success. Front Immunol. 2020;61:339.

    Google Scholar 

  9. Genton B, D’Acremont V, Rare L, Baea K, Reeder JC, Alpers MP, et al. Plasmodium vivax and mixed infections are associated with severe malaria in children: a prospective cohort study from Papua New Guinea. PLoS Med. 2008;5(6): e127.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Black J, Hommel M, Snounou G, Pinder M. Mixed infections with Plasmodium falciparum and P malariae and fever in malaria. The Lancet. 1994;343(8905):1095.

    Article  CAS  Google Scholar 

  11. McKenzie FE, Bossert WH. Mixed-species Plasmodium infections of humans. J Parasit. 1997;83(4):593.

    Article  CAS  PubMed  Google Scholar 

  12. Marques PX, Saúte F, Pinto VV, Cardoso S, Pinto J, Alonso PL, et al. Plasmodium species mixed infections in two areas of Manhiça District, Mozambique. Int J Biol Sci. 2005;1(3):96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Minakawa N, Dida GO, Sonye GO, Futami K, Njenga SM. Malaria vectors in Lake Victoria and adjacent habitats in western Kenya. PLoS ONE. 2012;7(3): e32725.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Idris ZM, Chan CW, Kongere J, Gitaka J, Logedi J, Omar A, et al. High and heterogeneous prevalence of asymptomatic and sub-microscopic malaria infections on islands in Lake Victoria. Kenya Sci Rep. 2016;6(1):1–13.

    Google Scholar 

  15. Akala HM, Watson OJ, Mitei KK, Juma DW, Verity R, Ingasia LA, et al. Plasmodium interspecies interactions during a period of increasing prevalence of Plasmodium ovale in symptomatic individuals seeking treatment: an observational study. Lancet Microbe. 2021;2(4):e141–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sitali L, Chipeta J, Miller JM, Moonga HB, Kumar N, Moss WJ, et al. Patterns of mixed Plasmodium species infections among children six years and under in selected malaria hyper-endemic communities of Zambia: population-based survey observations. BMC Infect Dis. 2015;15(1):204.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Molineaux L, Storey J, Cohen JE, Thomas A. A longitudinal study of human malaria in the West African Savanna in the absence of control measures: relationships between different Plasmodium species, in particular P. falciparum and P. malariae. Am J Trop Med Hyg. 1980;29(5):725–37.

    Article  CAS  PubMed  Google Scholar 

  18. Daniels RF, Deme AB, Gomis JF, Dieye B, Durfee K, Thwing JI, et al. Evidence of non-Plasmodium falciparum malaria infection in Kédougou. Sénégal Malar J. 2017;16:1–7.

    Google Scholar 

  19. Doderer-Lang C, Atchade PS, Meckert L, Haar E, Perrotey S, Filisetti D, et al. The ears of the African elephant: unexpected high seroprevalence of Plasmodium ovale and Plasmodium malariae in healthy populations in Western Africa. Malar J. 2014;13:1–8.

    Article  Google Scholar 

  20. Cattani JA, Tulloch JL, Vrbova H, Jolley D, Gibson FD, Moir JS, et al. The epidemiology of malaria in a population surrounding Madang, Papua New Guinea. Am J Trop Med Hyg. 1986;35(1):3–15.

    Article  CAS  PubMed  Google Scholar 

  21. 2019 Kenya Population and Housing Census Volume I: Population by County and Sub-County [Internet]. Kenya National Bureau of Statistics. https://www.knbs.or.ke/download/2019-kenya-population-and-housing-census-volume-i-population-by-county-and-sub-county/. Accessed30 Mar 2024

  22. Zhou G, Minakawa N, Githeko A, Yan G. Spatial distribution patterns of malaria vectors and sample size determination in spatially heterogeneous environments: a case study in the west Kenyan highland. J Med Entomol. 2004;41(6):1001–9.

    Article  PubMed  Google Scholar 

  23. Chaves LF, Taleo G, Kalkoa M, Kaneko A. Spleen rates in children: an old and new surveillance tool for malaria elimination initiatives in island settings. Trans R Soc Trop Med Hyg. 2011;105(4):226–31.

    Article  PubMed  Google Scholar 

  24. Isozumi R, Fukui M, Kaneko A, Chan CW, Kawamoto F, Kimura M. Improved detection of malaria cases in island settings of Vanuatu and Kenya by PCR that targets the Plasmodium mitochondrial cytochrome c oxidase III (cox3) gene. Parasitol Int. 2015;64(3):304–8.

    Article  CAS  PubMed  Google Scholar 

  25. World Health Organization. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Geneva: World Health Organization; 2011.

    Google Scholar 

  26. White NJ. Anaemia and malaria. Malar J. 2018;17(1):371.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Janovy J Jr, Clopton RE, Clopton DA, Snyder SD, Efting A, Krebs L. Species density distributions as null models for ecologically significant interactions of parasite species in an assemblage. Ecol Model. 1995;77(2–3):189–96.

    Article  Google Scholar 

  28. Mueller I, Widmer S, Michel D, Maraga S, McNamara DT, Kiniboro B, et al. High sensitivity detection of Plasmodium species reveals positive correlations between infections of different species, shifts in age distribution and reduced local variation in Papua New Guinea. Malar J. 2009;8(1):1–14.

    Article  Google Scholar 

  29. Pinto J, Sousa CA, Gil V, Goncalves L, Lopes D, do Rosario VE, et al. Mixed-species malaria infections in the human population of São Tomé island West Africa. Trans R Soc Trop Med Hyg. 2000;94(3):256–7.

    Article  CAS  PubMed  Google Scholar 

  30. Betson M, Clifford S, Stanton M, Kabatereine NB, Stothard JR. Emergence of nonfalciparum Plasmodium infection despite regular artemisinin combination therapy in an 18-month longitudinal study of Ugandan children and their mothers. J Infect Dis. 2018;217(7):1099–109.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Mehlotra RK, Lorry K, Kastens W, Miller SM, Alpers MP, Bockarie M, et al. Random distribution of mixed species malaria infections in Papua New Guinea. Am J Trop Med Hyg. 2000;62(2):225–31.

    Article  CAS  PubMed  Google Scholar 

  32. Mehlotra RK, Kasehagen LJ, Baisor M, Lorry K, Kazura JW, Bockarie MJ, et al. Malaria infections are randomly distributed in diverse holoendemic areas of Papua New Guinea. Am J Trop Med Hyg. 2002;67(6):555.

    Article  PubMed  Google Scholar 

  33. Mayxay M, Pukrittayakamee S, Newton PN, White NJ. Mixed-species malaria infections in humans. Trends Parasit. 2004;20(5):233–40.

    Article  Google Scholar 

  34. Haydon DT, Matthews L, Timms R, Colegrave N. Topndash;down or bottom–up regulation of intra–host blood–stage malaria: do malaria parasites most resemble the dynamics of prey or predator? Proc R Soc Lond B Biol Sci. 2003;270(1512):289–98.

    Article  Google Scholar 

  35. White NJ, Cook CC, Zumla A. Malaria Manson’s tropical diseases. Phila WB Saunders. 2003;1205:95.

    Google Scholar 

  36. McQueen PG, McKenzie FE. Competition for red blood cells can enhance Plasmodium vivax parasitemia in mixed-species malaria infections. Am J Trop Med Hyg. 2006;75(1):112.

    Article  PubMed  Google Scholar 

  37. Richie TL. Interactions between malaria parasites infecting the same vertebrate host. Parasitology. 1988;96(3):607–39.

    Article  PubMed  Google Scholar 

  38. Maitland K, Williams TN, Newbold CI. Plasmodium vevax and P. falciparum: biological interactions and the possibility of cross-species immunity. Parasit Today. 1997;13(6):227–31.

    Article  CAS  Google Scholar 

  39. Gunewardena DM, Carter R, Mendis KN. Patterns of acquired anti-malarial immunity in Sri Lanka. Mem Inst Oswaldo Cruz. 1994;89:63–5.

    Article  PubMed  Google Scholar 

  40. Bruce MC, Day KP. Cross-species regulation of Plasmodium parasitemia in semi-immune children from Papua New Guinea. Trends Parasit. 2003;19(6):271–7.

    Article  Google Scholar 

  41. Bruce MC, Macheso A, Kelly-Hope LA, Nkhoma S, McConnachie A, Molyneux ME. Effect of transmission setting and mixed species infections on clinical measures of malaria in Malawi. PLoS ONE. 2008;3(7): e2775.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Alifrangis M, Lemnge MM, Moon R, Theisen M, Bygbjerg I, Ridley RG, et al. IgG reactivities against recombinant Rhoptry-associated protein-1 (rRAP-1) are associated with mixed Plasmodium infections and protection against disease in Tanzanian children. Parasitology. 1999;119(4):337–42.

    Article  CAS  PubMed  Google Scholar 

  43. Kotepui M, Kotepui KU, De Jesus MG, Masangkay FR. Plasmodium spp. mixed infection leading to severe malaria: A systematic review and meta-analysis. Sci Rep. 2020;10(1):1–12.

    Article  Google Scholar 

  44. May J, Falusi AG, Mockenhaupt FP, Ademowo OG, Olumese PE, Bienzle U, et al. Impact of subpatent multi-species and multi-clonal plasmodial infections on anaemia in children from Nigeria. Trans R Soc Trop Med Hyg. 2000;94(4):399–403.

    Article  CAS  PubMed  Google Scholar 

  45. Cohen JE. Heterologous immunity in human malaria. Q Rev Biol. 1973;48(3):467–89.

    Article  CAS  PubMed  Google Scholar 

  46. Morishita K. Notes on Mixed Malarial Infection, with Special Reference to Antagonism among Different Species of Malarial Parasites and their Segregation by the Use of Special Drugs. 1931. https://www.cabidigitallibrary.org/doi/full/https://doiorg.publicaciones.saludcastillayleon.es/10.5555/19322900841. Accessed 8 Mar 2024

  47. McKenzie FE, Bossert WH. Multispecies Plasmodium infections of humans. J Parasitol. 1999;85(1):12.

    Article  CAS  PubMed  Google Scholar 

  48. Fontenille D, Lepers JP, Coluzzi M, Campbell GH, Rakotoarivony I, Coulanges P. Malaria transmission and vector biology on Sainte Marie Island. Madagascar J Med Entomol. 1992;29(2):197–202.

    Article  CAS  PubMed  Google Scholar 

  49. Okell LC, Bousema T, Griffin JT, Ouédraogo AL, Ghani AC, Drakeley CJ. Factors determining the occurrence of submicroscopic malaria infections and their relevance for control. Nat Commun. 2012;3(1):1237.

    Article  PubMed  Google Scholar 

  50. Idris ZM, Chan CW, Kongere J, Hall T, Logedi J, Gitaka J, et al. Naturally acquired antibody response to Plasmodium falciparum describes heterogeneity in transmission on islands in Lake Victoria. Sci Rep. 2017;7(1):9123.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We want to express our thanks to the communities and their leaders for their invaluable support and involvement in the surveys. We sincerely appreciate the dedication of every member of the field team. Special gratitude goes to Mayumi Fukui and Ikuko Kusuda from Osaka Metropolitan University for their assistance with conducting the PCR assays. Additionally, we extend our thanks to Tomomi Kuwana and Naito Satoko for their pivotal roles in survey management and logistics.

Funding

Open access funding provided by Karolinska Institute. This work (co-P.Is: A.K and J.G) was supported by JICA/AMED joint research project (SATREPS) (Grant no. 20JM0110020H0002), Hitachi Fund Support for Research Related to Infectious Diseases and Japan Society for Promotion of Science (JSPS) Kakenhi grant (22K0129). P.O is supported by The Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan.

Author information

Author notes

  1. Jesse Gitaka and Akira Kaneko have Joint senior authors.

Authors and Affiliations

  1. Department of Virology, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan

    Protus Omondi, Brian Musyoka, Takatsugu Okai & Yasutoshi Kido

  2. Department of Parasitology/ Osaka International Research Center for Infectious Diseases, Osaka Metropolitan University, Osaka, Japan

    James Kongere, Chim W. Chan & Akira Kaneko

  3. Department of Eco-Epidemiology, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan

    Wataru Kagaya

  4. Department of Clinical Medicine, Mount Kenya University, Thika, Kenya

    Mtakai Ngara,  Bernard N. Kanoi & Jesse Gitaka

  5. Island Malaria Group, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden

    Mtakai Ngara & Akira Kaneko

Authors
  1. Protus Omondi
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Brian Musyoka
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Takatsugu Okai
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. James Kongere
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Wataru Kagaya
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Chim W. Chan
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Mtakai Ngara
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Bernard N. Kanoi
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Yasutoshi Kido
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Jesse Gitaka
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Akira Kaneko
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

P.O, B.M, C.W.C, T.O, W.K, J.K, J.G and A.K formulated and designed the experiments, P.O, C.W.C, B.M, T.O, W.K, J.K and A.K, performed the experiments, P.O, C.W.C, B.M, W.K, Y.K, M.N, B.N.K, J.G, and A.K contributed to the analysing and interpretation of the data. P.O, and A.K wrote the paper. All authors reviewed and approved the manuscript.

Corresponding author

Correspondence to Akira Kaneko.

Ethics declarations

Competing interests

All authors have declared no competing of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Omondi, P., Musyoka, B., Okai, T. et al. Non-random distribution of Plasmodium Species infections and associated clinical features in children in the lake Victoria region, Kenya, 2012–2018. Trop Med Health 52, 52 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41182-024-00622-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s41182-024-00622-3

Keywords

Tropical Medicine and Health

ISSN: 1349-4147

Contact us