Malaria continues to represent one of the most formidable infectious disease challenges confronting global public health, with a disproportionate burden borne by children under five years in sub-Saharan Africa and South Asia. According to the World Malaria Report 2021, there were an estimated 241 million malaria cases and 627,000 deaths worldwide in 2020, representing an increase compared to preceding years, largely attributable to disruptions caused by the COVID-19 pandemic to malaria prevention and treatment services [1]. India accounts for approximately 2% of the global malaria burden but harbours nearly 88% of all malaria cases in the South-East Asian Region, rendering it the most endemic country in this zone [2]. Among Indian states, Telangana and Andhra Pradesh in southern India have historically reported significant proportions of malaria transmission, with both Plasmodium falciparum and Plasmodium vivax circulating endemically [3]. The diverse ecology of these regions, encompassing irrigated agricultural zones, urban peripheries, and forested tribal belts, sustains persistent Anopheles mosquito breeding and facilitates year-round malaria transmission [4].

Severe malaria, as defined by the World Health Organization (WHO), is a multisystem disorder characterised by impaired consciousness, respiratory distress, severe anaemia, hypoglycaemia, prostration, hyperparasitaemia, abnormal bleeding, circulatory collapse, or the presence of haemoglobinuria in a patient with confirmed malaria parasitaemia [5]. While Plasmodium falciparum is the principal aetiological agent of severe and fatal malaria, increasingly, P. vivax has been recognised as capable of causing severe disease in vulnerable populations, including young children [6]. In the paediatric population, the clinical expression of severe malaria differs substantially from adults, with cerebral malaria, severe malarial anaemia, and respiratory distress syndrome being the predominant life-threatening manifestations [7]. Children in this age group lack acquired immunity and are especially susceptible to rapid clinical deterioration, often within hours of onset of fever, necessitating early diagnosis and appropriate hospitalisation [8].

Several host, parasitological, and environmental factors have been identified in the literature as significant contributors to the risk of developing severe malaria in children. Nutritional deficiency, particularly protein-energy malnutrition, impairs immune function and erythrocyte integrity, thereby increasing susceptibility to high-density parasitaemia and haematological complications [9]. Young age, particularly the first two years of life, is a well-recognised vulnerability window during which passive maternal immunity wanes and active immunity has not yet been acquired [10]. Lack of appropriate preventive interventions, including insecticide-treated bed net use, indoor residual spraying, and timely vaccination where applicable, further predisposes children in endemic rural communities to recurrent and severe malarial episodes [11]. Additionally, delayed health-seeking behaviour, compounded by geographic remoteness and socioeconomic constraints, allows uncomplicated malaria to progress to severe systemic disease in many low-resource settings [12].

Despite the recognition of malaria as a public health priority in India, limited prospective data exist from tertiary referral centres in Telangana and Andhra Pradesh specifically examining risk factors for severe malaria in the paediatric age group. Most existing studies are retrospective, geographically confined to northern or north-eastern India, or focus exclusively on P. falciparum without accounting for the significant burden of P. vivax and mixed infections in southern India [13]. The present study was therefore designed to prospectively characterise the burden, clinical spectrum, and independent risk factors associated with severe malaria in children aged 6 months to 12 years presenting to two tertiary care institutions in Hyderabad and Nellore, thereby contributing region-specific evidence to inform clinical management and public health strategies in southern India [14].

2. OBJECTIVES

The primary objective of this study was to determine the proportion of severe malaria among children aged 6 months to 12 years presenting with confirmed malaria parasitaemia to tertiary care hospitals in Hyderabad, Telangana and Nellore, Andhra Pradesh between May 2021 and March 2022, and to identify and quantify independent clinical, demographic, haematological, and parasitological risk factors associated with the development of severe malaria in this paediatric cohort, using WHO 2015 criteria for case classification.

The secondary objectives were to describe the clinical and laboratory profile of severe versus non-severe malaria in children, to determine the species-specific contribution to severe disease, and to evaluate the prognostic significance of malnutrition, age, vaccination status, residential locality, and parasite density as risk factors for severe malaria, thereby providing evidence-based recommendations for early identification and targeted management of high-risk paediatric patients in similar tertiary care settings across southern India.

Study Design and Setting This was a hospital-based prospective observational study conducted over a period of eleven months from May 2021 to March 2022. The study was carried out at two tertiary care institutions: the Department of Paediatrics, Malla Reddy Medical College for Women, Suraram, Hyderabad, Telangana, and the Department of Gastroenterology and General Medicine at Narayana Medical College Hospital, Nellore, Andhra Pradesh. Both institutions function as major referral centres receiving patients from urban, peri-urban, and rural areas of their respective catchment regions. Ethical clearance was obtained from the Institutional Ethics Committees of both participating institutions prior to commencement of the study (Reference: MRMCW/IEC/2021/04 and NMC/IEC/2021/07). Written informed consent was obtained from parents or legal guardians of all enrolled children, and assent was obtained from children aged ≥7 years where appropriate. The study was conducted in accordance with the Declaration of Helsinki (2013 revision) [15]. Study Population and Sampling All children aged 6 months to 12 years presenting with fever and confirmed malaria parasitaemia by peripheral blood smear microscopy or rapid diagnostic test (RDT) during the study period were considered for enrolment. A convenient consecutive sampling technique was employed, and all eligible children meeting the inclusion criteria were enrolled until the target sample size of 60 was achieved. Peripheral blood smear examination was performed using Giemsa-stained thick and thin films, examined by two independent trained microscopists. RDT using the SD BIOLINE Malaria Ag P.f/Pan kit was performed for all smear-positive and selected high-suspicion smear-negative cases, and the higher-sensitivity result was used for final classification. Parasitaemia was quantified per 200 white blood cells on thick film and expressed per microlitre of blood. Children were classified into severe malaria (n=38) and non-severe malaria (n=22) groups according to the WHO 2015 operational criteria for severe P. falciparum malaria, which were adapted for application to all Plasmodium species in this study, consistent with evolving evidence on non-falciparum severe malaria [5,6]. Data Collection, Statistical Analysis, and Ethical Considerations A pre-designed, pre-tested structured case record form was used to capture data on age, sex, weight, height, mid-upper arm circumference (MUAC), nutritional status, immunisation history, residential locality, duration of illness prior to hospital presentation, clinical features at admission, treatment received prior to referral, and laboratory investigations. Nutritional status was classified according to WHO 2006/2007 growth reference standards: severe acute malnutrition (SAM) was defined as weight-for-height Z-score <−3 SD or MUAC <115 mm; moderate acute malnutrition (MAM) as WHZ between −3 and −2 SD or MUAC 115–125 mm; and normal nutritional status as WHZ ≥−2 SD. Haematological investigations (full blood count, peripheral smear), blood biochemistry (random blood glucose, serum creatinine, liver function tests, serum electrolytes), and coagulation profiles were performed at admission for all enrolled children using standardised laboratory protocols. Data were entered into Microsoft Excel 2019 and analysed using SPSS version 26.0 (IBM Corp., Armonk, NY). Descriptive statistics were reported as mean ± standard deviation (SD) for continuous variables and frequencies with percentages for categorical variables. Chi-square test or Fisher's exact test was applied for comparison of categorical variables between severe and non-severe malaria groups. Independent samples t-test was used for continuous variables. Variables achieving significance at p<0.10 in univariate analysis were entered into a multivariate binary logistic regression model using a backward stepwise likelihood ratio method to identify independent predictors of severe malaria. Odds ratios (OR) with 95% confidence intervals (CI) are reported. A two-tailed p-value of <0.05 was considered statistically significant throughout. Inclusion Criteria (1) Children aged 6 months to 12 years (completed); (2) confirmed malaria parasitaemia on peripheral blood smear microscopy (Giemsa-stained thick and thin film) or positive RDT for Plasmodium species; (3) fever ≥38.0°C documented at admission or history of fever within the preceding 48 hours; (4) children admitted to the inpatient paediatric ward or intensive care unit; (5) availability of parent/guardian to provide written informed consent. Exclusion Criteria (1) Children with confirmed concurrent bacterial or viral co-infections at the time of enrolment (e.g., confirmed dengue fever, typhoid, bacterial meningitis) based on appropriate confirmatory tests; (2) children with known pre-existing haematological disorders (e.g., sickle cell disease, thalassaemia major); (3) children already receiving antimalarial treatment for ≥48 hours prior to blood sampling; (4) incomplete data or failure to obtain informed consent; (5) children aged less than 6 months or above 12 years (completed). Data Collection Procedure Data collection was initiated within 6 hours of admission. A trained research coordinator under the supervision of a paediatric consultant completed the structured case record form. Clinical examination findings, vital signs, Glasgow Coma Scale or Blantyre Coma Scale scores, and nutritional assessments were recorded systematically. Blood samples were collected under aseptic conditions for all relevant laboratory investigations at a single time point at admission to minimise variability. All laboratory investigations were processed in the respective institutional laboratories which comply with national quality assurance standards. Statistical Data Analysis Univariate analysis was performed first to screen potential risk factors, followed by multivariate binary logistic regression for independent predictors. The Hosmer-Lemeshow goodness-of-fit test was used to assess model calibration; the model demonstrated adequate fit (p=0.418). Receiver operating characteristic (ROC) analysis was performed to evaluate the overall discriminative ability of the regression model. All statistical tests were two-tailed and significance was set at p<0.05

A total of 60 children with confirmed malaria were enrolled during the study period of May 2021 to March 2022. Of the 60 children, 38 (63.3%) fulfilled WHO 2015 criteria for severe malaria and 22 (36.7%) were classified as non-severe malaria. The mean age of the study population was 48.8 ± 27.4 months. Male children accounted for 61.7% (n=37) of the cohort. The majority of enrolled children (68.3%) were from rural backgrounds. As shown in Table 1, children with severe malaria showed significantly higher rates of severe acute malnutrition (47.4% vs 18.2%; p=0.021), rural residence (76.3% vs 54.5%; p=0.048), and incomplete EPI vaccination (44.7% vs 22.7%; p=0.036) compared to the non-severe group. The proportion of children in the youngest age group (6–24 months) was significantly higher in the severe malaria group (36.8% vs 27.3%; p=0.042). Sex distribution did not differ significantly between the two groups (p=0.742).

Regarding parasite species distribution (Table 2), Plasmodium falciparum was the most common species overall (60.0%; n=36), and its prevalence was significantly higher in severe malaria cases (73.7% vs 36.4%; p=0.003). P. vivax accounted for 30.0% (n=18) of infections and was more prevalent in the non-severe group (45.4% vs 21.1%; p=0.041). Mixed infections were present in 10.0% (n=6) of cases. High parasite density (>100,000/µL) was documented in 52.6% of severe cases versus 9.1% of non-severe cases (p<0.001). The clinical manifestations of severe malaria are summarised in Table 3. Severe anaemia (Hb <5 g/dL) was the most common severe manifestation (47.4%), followed by cerebral malaria (36.8%), respiratory distress (42.1%), and hypoglycaemia (31.6%). Acute kidney injury was observed exclusively in the severe group (21.1%). Multiple overlapping severe features were present in 24 of 38 (63.2%) children with severe malaria, indicating multisystem involvement. Laboratory parameters are presented in Table 4 and demonstrated significantly lower haemoglobin, platelet counts, and blood glucose, and higher creatinine and bilirubin values in the severe malaria group compared to the non-severe group (all p<0.05).

On multivariate logistic regression analysis (Table 5), the following variables emerged as independent risk factors for severe malaria: P. falciparum infection (adjusted OR 4.12; 95% CI 1.62–10.48; p=0.003), parasite density >100,000/µL (adjusted OR 4.98; 95% CI 1.84–13.42; p<0.001), severe acute malnutrition (adjusted OR 3.46; 95% CI 1.24–9.62; p=0.021), delayed hospital presentation >72 hours (adjusted OR 2.84; 95% CI 1.18–6.84; p=0.028), incomplete vaccination status (adjusted OR 2.48; 95% CI 1.06–5.82; p=0.036), age group 6–24 months (adjusted OR 2.06; 95% CI 1.02–4.18; p=0.042), and rural residence (adjusted OR 2.14; 95% CI 1.04–4.40; p=0.048). The overall model was significant (χ²=42.86; df=7; p<0.001) and the Nagelkerke R² was 0.614, indicating good explanatory power. The ROC curve analysis yielded an AUC of 0.879 (95% CI 0.793–0.964), demonstrating excellent discriminative ability of the model. Six children (15.8%) in the severe malaria group required paediatric intensive care unit (PICU) admission, and there were 4 deaths (10.5% case fatality rate in severe group; 6.7% overall).

Table 1: Demographic and Clinical Profile of Study Children Stratified by Malaria Severity

SAM=Severe Acute Malnutrition; MAM=Moderate Acute Malnutrition; EPI=Expanded Programme on Immunisation; SD=Standard Deviation. Statistically significant values (p<0.05) shown in bold.

Table 2: Plasmodium Species Distribution and Parasite Density in Study Children

RBC=Red Blood Cells. Species identification based on Giemsa-stained peripheral blood smear and RDT.

Table 3: Clinical Manifestations of Severe versus Non-Severe Malaria in Study Children

Hb=Haemoglobin; RBC=Red Blood Cells. Multiple severe features co-existed in 24/38 (63.2%) of severe malaria cases.

Table 4: Laboratory Parameters at Admission in Severe and Non-Severe Malaria Groups

WBC=White Blood Cells; ALT=Alanine Aminotransferase; SD=Standard Deviation. Values expressed as Mean ± SD. p-values from independent samples t-test.

Table 5: Multivariate Logistic Regression Analysis – Independent Risk Factors for Severe Malaria

OR=Odds Ratio; CI=Confidence Interval. Adjusted ORs derived from backward stepwise logistic regression. Model AUC=0.879; Nagelkerke R²=0.614; Hosmer-Lemeshow p=0.418.

Forest-style horizontal bar chart displaying the adjusted odds ratios (aOR) with 95% confidence intervals (CI) for seven independent risk factors associated with severe malaria, derived from multivariate binary logistic regression analysis using a backward stepwise likelihood ratio method. Data are from 60 children admitted with confirmed malaria parasitaemia at Malla Reddy Medical College for Women, Hyderabad and Narayana Medical College, Nellore, India (May 2021 – March 2022). Risk factors are ranked in descending order of aOR. The red dashed vertical reference line at OR = 1.0 denotes the null effect threshold; bars extending beyond this line indicate increased risk of severe malaria. Error bars represent the lower and upper bounds of the 95% CI. Parasite density >100,000/µL was the strongest independent predictor (aOR 4.98; 95% CI 1.84–13.42; p<0.001), followed by Plasmodium falciparum infection (aOR 4.12; 95% CI 1.62–10.48; p=0.003) and severe acute malnutrition (aOR 3.46; 95% CI 1.24–9.62; p=0.021). All variables achieved statistical significance at p<0.05. Overall model discrimination: AUC = 0.879 (95% CI 0.793–0.964); Nagelkerke R² = 0.614; Hosmer–Lemeshow goodness-of-fit p = 0.418.

Figure 1: Independent Risk Factors for Severe Malaria in Children Aged 6 Months to 12 Years - Multivariate Logistic Regression Analysis

Abbreviations: aOR = Adjusted Odds Ratio; CI = Confidence Interval; OR = Odds Ratio; SAM = Severe Acute Malnutrition; AUC = Area Under the Receiver Operating Characteristic Curve.

Donut pie chart illustrating the proportional distribution of eight WHO-defined severe malaria manifestations documented among the 38 children fulfilling criteria for severe malaria at admission, as a percentage of the severe malaria group (n=38). Cases were classified according to WHO 2015 operational criteria for severe malaria, adapted for all Plasmodium species. Severe anaemia (haemoglobin <5 g/dL) was the most prevalent manifestation, identified in 18 children (47.4%), followed by respiratory distress (n=16; 42.1%), cerebral malaria (n=14; 36.8%), and hypoglycaemia (blood glucose <2.2 mmol/L; n=12; 31.6%). Hyperparasitaemia (>5% parasitised red blood cells) was observed in 10 cases (26.3%), convulsions (≥2 episodes) in 9 cases (23.7%), acute kidney injury in 8 cases (21.1%), and circulatory shock in 6 cases (15.8%). Multiple overlapping severe features co-existed in 24 of 38 (63.2%) children with severe malaria, indicating multisystem involvement; therefore, percentages reflect individual manifestation frequencies and do not sum to 100%.

Figure 2: Distribution of Severe Clinical Manifestations Among Children with Severe Malaria

Abbreviations: Hb = Haemoglobin; RBC = Red Blood Cells; WHO = World Health Organization.

The present study provides prospective, region-specific data on the risk factors for severe malaria in hospitalised children in two major tertiary care centres in Telangana and Andhra Pradesh, India, over a period of eleven months spanning the high-transmission seasons of 2021–2022. The finding that 63.3% of enrolled malaria cases fulfilled criteria for severe disease is higher than figures reported from community-based studies in India but consistent with the high-risk profiles expected in children presenting to tertiary referral hospitals, which receive predominantly complicated or treatment-refractory cases [3,4]. The overall case fatality rate of 6.7% (10.5% in severe cases) is comparable to rates reported from similar tertiary care studies in India and reflects the advanced stage of disease at presentation typical in resource-limited settings where home management and delayed care-seeking are common [7,12]. Our findings underscore the critical importance of early recognition and prompt referral of children with malaria, particularly those belonging to high-risk demographic groups.

The dominance of P. falciparum as the aetiological agent of severe malaria (73.7% of severe cases) and its identification as the strongest independent predictor of severe disease (adjusted OR 4.12; p=0.003) is consistent with extensive global literature on malaria pathophysiology, wherein the unique capacity of P. falciparum-infected erythrocytes for cytoadherence, rosetting, and sequestration in microvascular beds underlies the pathogenesis of cerebral malaria, metabolic acidosis, and multi-organ dysfunction [5,8]. The high parasite density threshold (>100,000/µL) as the single strongest predictor of severe malaria (adjusted OR 4.98; p<0.001) corroborates findings from seminal studies in African and South Asian children, confirming that hyperparasitaemia is both a marker and mediator of severe disease through immunopathological mechanisms including excessive inflammatory cytokine release, erythrophagocytosis, and haemolysis [9,10]. Notably, 21.1% of severe cases in this study were attributable to P. vivax, including cases of severe anaemia and respiratory distress, consistent with a growing body of evidence challenging the historical notion of P. vivax as a 'benign' malaria species and supporting the WHO recommendation to apply severe malaria criteria to non-falciparum species [6].

Severe acute malnutrition emerged as a significant independent risk factor for severe malaria (adjusted OR 3.46; p=0.021), with SAM present in 47.4% of severe cases compared to 18.2% in non-severe cases. This relationship is pathophysiologically multidimensional: malnutrition impairs both innate and adaptive immune responses, including neutrophil function, complement activation, and T-cell-mediated cytokine responses essential for parasite clearance; simultaneously, it reduces the integrity of the gut epithelial barrier, potentially enhancing translocation of bacterial lipopolysaccharides that exacerbate the systemic inflammatory response to malaria [11,13]. The interplay between malnutrition and anaemia is particularly relevant, as iron deficiency anaemia endemic in malnourished Indian children lowers the haemoglobin threshold at which malarial haemolysis precipitates severe anaemia [9]. Our finding that 47.4% of severe malaria cases had Hb <5 g/dL aligns with the documented synergism between malnutrition and malarial anaemia severity. The identification of age 6–24 months as an independent risk factor (adjusted OR 2.06; p=0.042) reflects the well-established immunological vulnerability of this age group, in which maternally transferred antimalarial immunity declines during the first year of life and active adaptive immunity against Plasmodium antigens has not yet developed through cumulative exposure [10,14]. Incomplete vaccination status was independently associated with severe malaria (adjusted OR 2.48; p=0.036), an association that may reflect shared socioeconomic and access-to-care determinants, since inadequate immunisation coverage often co-exists with limited health literacy, rural isolation, and poverty conditions that collectively compound the risk of severe infectious diseases [11]. Delayed presentation (>72 hours) as an independent risk factor (adjusted OR 2.84; p=0.028) highlights the critical window for therapeutic intervention in malaria, wherein each 24-hour delay in effective antimalarial treatment is associated with exponential parasite multiplication, increasing risk of cerebral sequestration, anaemia, and metabolic derangements [12,15].

6. LIMITATIONS OF THE STUDY

This study has several limitations that warrant acknowledgment. First, the relatively modest sample size of 60 children, albeit adequate for primary objectives, limits the statistical power for subgroup analyses, particularly for rare severe malaria manifestations such as haemoglobinuria and abnormal bleeding. Second, the study was conducted at two tertiary care referral hospitals, introducing significant selection bias, as children presenting to tertiary centres represent a pre-selected high-risk population not representative of community-level malaria burden. This limits the generalisability of prevalence estimates to the broader population. Third, as a single-season study conducted primarily during 2021–2022, the findings may not fully capture seasonal variability in malaria transmission intensity and species distribution, and the study period coincided with the ongoing COVID-19 pandemic, which may have influenced care-seeking patterns and hospital attendance. Fourth, the study relied on peripheral blood smear microscopy supplemented by RDT for parasitological diagnosis; more sensitive molecular techniques such as polymerase chain reaction (PCR) were not employed, which may have resulted in underdetection of low-density parasitaemia and mixed infections. Fifth, socioeconomic indicators such as household income, parental education, and bed net usage important confounders in the malaria-malnutrition-severity relationship were incompletely captured in the case record form. Finally, the cross-sectional nature of parasite density measurement at admission does not account for pre-hospitalisation parasite dynamics, and prior partial antimalarial treatment in referred patients may have reduced parasite density at the time of measurement, potentially underestimating its true association with severe disease.

ACKNOWLEDGMENT

The authors express their sincere gratitude to the children and their families who participated in this study and consented to data collection under difficult circumstances. We gratefully acknowledge the dedicated nursing staff and laboratory technicians of the Paediatric Ward and Clinical Pathology Laboratory at Malla Reddy Medical College for Women, Hyderabad and Narayana Medical College Hospital, Nellore, whose meticulous work in blood smear preparation, laboratory investigations, and patient care was indispensable to the conduct of this study. We also thank the Institutional Ethics Committees of both institutions for their timely review and approval. The study received no external funding and was supported solely through institutional resources. There are no conflicts of interest to declare.

This prospective study conducted across two tertiary care institutions in Hyderabad and Nellore, southern India, has demonstrated that severe malaria constitutes a substantial proportion of paediatric malaria admissions in this region, with 63.3% of enrolled children fulfilling WHO criteria for severe disease. The study has systematically identified and quantified seven independent risk factors for severe malaria in children aged 6 months to 12 years: Plasmodium falciparum infection, high parasite density (>100,000/µL), severe acute malnutrition, delayed hospital presentation (>72 hours), incomplete EPI vaccination, age 6–24 months, and rural residence. The co-existence of multiple risk factors in individual children particularly SAM combined with P. falciparum infection and high parasite density was strongly associated with multisystem severe malaria manifestations and higher case fatality. Severe anaemia and cerebral malaria were the most prevalent severe manifestations, occurring in 47.4% and 36.8% of severe cases respectively, consistent with the high nutritional vulnerability and young age of the study population. The logistic regression model demonstrated excellent discriminative ability (AUC 0.879), suggesting that these seven risk factors together can serve as a practical clinical risk stratification tool at the point of hospital admission. The findings of this study carry direct implications for clinical practice and public health policy in malaria-endemic regions of southern India. Clinically, prompt identification of children with any combination of these risk factors should trigger immediate intensive monitoring, early initiation of parenteral antimalarial therapy as per national guidelines, aggressive correction of hypoglycaemia and anaemia, and timely nutritional rehabilitation. The strong independent association between SAM and severe malaria reinforces the need for integrated malaria and nutrition programming, including routine malnutrition screening at malaria diagnosis and vice versa. From a public health perspective, targeted community-level interventions including strengthening of EPI services in rural areas, community health worker-led sensitisation on early fever recognition and prompt care-seeking, expanded access to RDTs at primary health centres, and intensified vector control in high-burden rural communities are essential to interrupt the chain of events leading from uncomplicated febrile illness to preventable paediatric death. Future multicentre prospective studies with larger sample sizes encompassing multiple transmission seasons and incorporating molecular diagnostics, socioeconomic profiling, and long-term follow-up are warranted to further refine the evidence base for severe malaria risk stratification and intervention in the Indian paediatric population [14,15]. Conflict of Interest: None declared Source of Funding: Nil Ethical Approval: Obtained from IEC of both institutions

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