Epidemiology of malaria in Chhattisgarh, India: a surveillance data analysis, 2015–2023

Abstract

Background

India accounts for two-thirds of the malaria burden in Southeast Asia. We described the lab-confirmed malaria cases under the Integrated Disease Surveillance Programme in Chhattisgarh, India, from 2015 to 2023.

Methods

We conducted a surveillance data analysis by abstracting the lab-confirmed malaria cases from five regions of Chhattisgarh from January 2015 to December 2023. We estimated the annual parasite incidence (API) by region and year. We estimated the incidence rate ratio (IRR) with a 95% CI over the years using a generalized estimating equation in Stata 16.0.

Results

A total of 391 387 malaria cases were reported from 2015 to 2023. API ranged from 0.4–3.2 per 1000 population with an annual decline of 25% (IRR:0.75; 95% CI 0.71 to 0.79). Cases peaked in July (monsoon season) and November. Incidence was consistently higher in Chhattisgarh's Bastar (IRR:12.5; 95% CI 3.7 to 43.0) and Surguja regions (IRR:7.4; 95% CI 2.0 to 27.4) compared with the central region.

Conclusions

Southern districts of Chhattisgarh consistently documented increased incidence over the years. We recommend strengthening the implementation of the vector control measures starting in May. Further research should be conducted to identify the reasons for the high malaria incidence in southern Chhattisgarh.

Introduction

In 2022, the Southeast Asia region contributed approximately 2% of global malaria cases.¹ Although the malaria burden in the region witnessed a substantial decline of 76% over the span of two decades, from 2000 to 2022, 66% of cases occurred in India. India accounts for two-thirds of the malaria deaths in the Southeast Asia region.¹ About 80% of malaria reported in India is confined to 20% of the population residing in tribal and hilly areas.² Chhattisgarh is a centrally located state in India, with 32% of its population residing in tribal and forested areas. The state comprised only 2.29% of India's population but contributed to 18% of malaria cases and 40% of malaria-related deaths in the country.^3,4

Since 2006 in India, malaria cases have been reported in the Integrated Disease Surveillance Programme (IDSP) with a ‘bottoms-up approach’ by weekly aggregating data reporting. The Integrated Health Information Platform (IHIP), a dedicated web-based platform of the IDSP, was launched in 2021 to improve the daily reporting of cases. The IHIP captures case-based reporting almost in real time from the reporting facilities. Chhattisgarh is one of the states in India that commenced reporting in the IHIP system in April 2021.⁵

With the case-based daily reporting of malaria, the IHIP provides analyzable data to describe the trends, patterns and geographical distribution. This information aids in identifying high-risk areas, allocating resources effectively and implementing targeted public health interventions.

We described the lab-confirmed malaria cases of IDSP-IHIP by year, district, age and gender in Chhattisgarh from 2015 to 2023.

Materials and methods

Study design, setting and period

We conducted a cross-sectional study by analyzing the malaria surveillance data in Chhattisgarh, India, from 2015 to 2023. Chhattisgarh is a centrally located state in India, with a population of approximately 30 million people. Chhattisgarh borders seven states and receives rainfall from July to September. As of 2021, Chhattisgarh has five divisions with 28 administrative districts, that is, the divisions are organized from north to south as follows: Division One is called Surguja, with five districts; Division Two is Bilaspur, with six districts; Division Three, Durg, has five districts; Division Four, Raipur, has five districts; and Division Five, Bastar, consists of seven districts.

Data sources

We used two different data sources for the analysis.

First, we used the weekly aggregate data on lab-confirmed malaria cases and deaths reported in the Laboratory reporting form (L-form) of the IDSP from January 2015 to March 2021. The information was sourced from the Chhattisgarh State Surveillance Unit, where weekly malaria data from all districts are reported, compiled and subsequently reported to the Central Surveillance Unit, India.

Second, we used a de-identified line list of lab-confirmed malaria cases and deaths reported under the IHIP from April 2021 to December 2023. The line list of cases and deaths includes age, gender, district and reporting date.

Operational definition

A lab-confirmed malaria case is an individual who tested positive either by Rapid Diagnostic Kit (SD Biosensor Ag kit, approved by the Ministry of Health & Family Welfare) or demonstration of a malaria parasite by light microscopy on the peripheral blood smear.

Data analysis

We estimated the annual parasite incidence (API) of malaria cases (per 1000 population) by dividing the number of new reported cases by the total estimated population by year and district. We classified the API into four groups—<1, 1 to <2, 2 to <5 and ≥5 per 1000 population—for grading the malaria incidence in each district. The test positivity rate (TPR) was calculated by dividing the number of lab-confirmed cases by the total number of tests conducted and is expressed as a percentage. Additionally, we determined the proportion of Plasmodium falciparum cases among the total reported malaria cases. We estimated the case fatality rate (CFR) by dividing total deaths by the cases reported and this is expressed as a percentage. The annual blood examination rate (ABER) per 100 population was estimated by dividing the total tested by the projected population. The malaria line-list cases reported in the IHIP were distributed by age and gender. We used a generalized estimating equation (GEE) to estimate the significance of the change in malaria incidence across the region over the years. Because each district reports the incidence over the years (clustered and dependent), we used the GEE to adjust for clustering at the regional level. We estimated the incidence rate ratio (IRR) with a 95% CI. We cleaned the data with Microsoft Excel and analyzed it using Stata 16.0 (StataCorp LLC, Lakeway Drive, College Station, Texas 77845-4512, USA). We visualized the incidence by district using maps created with Datawrapper.

Results

A total of 391 387 malaria cases were reported from 2015 to 2023. Among these, 34 768 cases were reported by the IHIP from April 2021 to December 2023. The incidence of malaria increased from 2.9 to 3.2 per 1000 population in 2015 and 2017, respectively, and thereafter, it declined to 0.4 in 2021. By 2023, the API had increased to 0.6 cases per 1000 population (Figure 1). On analyzing the seasonal pattern for 2015 to 2023, the cases peaked in July, and most cases were reported in the third and fourth quarters (Figure 2). The API was consistently higher in Chhattisgarh's southern districts (Bastar region), including Sukma, Baster, Bijapur, Narayanpur and Kondagaon. Of the above, API declined in the Kanker district between 2015 and 2023. Similarly, the API decreased in the northern districts of Chhattisgarh, including Koriya, Jashpur, Surguja, Korba and Raigarh, from 2015 to 2019 and has remained <1 per 1000 population since 2020 (Figure 3 and Supplementary Figure 1). API ranged between 0.4 and 3.2 during 2015 and 2023, with an annual decline of 25% (IRR:0.75; 95% CI 0.71 to 0.79). Incidence was consistently higher in Chhattisgarh's southern (IRR:12.5; 95% CI 3.7 to 43.0) and northern regions (IRR:7.4; 95% CI 2.0 to 27.4) compared with the central region (Table 1 and Supplementary Table 1).

Figure 1.

Distribution of API per 1000 population and ABER over the years, Chhattisgarh, India, 2015–2023.

Figure 2.

Trend of malaria cases by year, Chhattisgarh, India, 2015–2023.

Figure 3.

Distribution of annual parasite incidence (API) per 1000 population by district, Chhattisgarh, India, 2015–2023.

Table 1.

Comparison of change in malaria incidence across the divisions in Chhattisgarh, India, 2015–2023

Division	Population	Unadjusted incidence rate ratio	95% CI	p	Adjusted incidence rate ratio*	95% CI	p
Raipur (Division 4, Central)	4 466 525	Ref.			Ref.
Surguja (Division 1, Northern)	8 542 857	5.6	1.41 to 21.93	0.0	7.4	2.00 to 27.43	0.0
Bilaspur (Division 2)	6 581 874	1.7	0.37 to 7.26	0.8	2.3	0.62 to 8.36	0.2
Durg (Division 3, Western)	6 804 454	1.4	0.29 to 6.86	0.9	1.8	0.46 to 7.14	0.4
Bastar (Division 5, Southern)	3 566 815	19.8	5.51 to 71.2	0.0	12.5	3.66 to 42.99	0.0

*Generalized estimating equation analysis conducted by adjusting for the year of reporting (2015–2023) and the administrative districts.

The ABER declined from 6.1 in 2017 to 0.6 in 2021, then increased to 1.5 in 2023. The TPR decreased from 6.2 in 2015 to 3.8 in 2020, then increased to 5.7 in 2023 (Table 2). Of the 391 387 malaria cases, 311 313 (79.5%) were positive for P. falciparum. The proportion of P. falciparum cases increased over the years from 79% in 2015 to 87% in 2023. The burden of mixed plasmodium cases has more than doubled over the last 3 y (from 208 in 2021 to 435 in 2023) (Figure 4). Overall, 336 malaria deaths were reported from 2015 to 2023. The CFR remained about 0.1% from 2016 to 2020 and peaked in 2021 (0.4%, 34/9713). No deaths were reported during 2022 and 2023 as per the reporting dashboard under IHIP.

Table 2.

Test positivity rate by year, Chhattisgarh, India, 2015–2023

Year	Number of malaria cases	Number tested for malaria	Test positivity rate (per 100 tested)
2015	74 387	1 200 546	6.2
2016	78 176	1 469 383	5.3
2017	82 576	1 588 197	5.2
2018	50 807	1 347 748	3.8
2019	42 210	1 570 832	2.7
2020	24 558	653 098	3.8
2021	9713	162 598	3.7
2022	12 194	267 620	4.7
2023	16 766	409 987	5.7

Figure 4.

Trend of Plasmodium falciparum cases by year, Chhattisgarh, India, 2015–2023.

Characteristics of malaria cases reported under the IHIP, April 2021–December 2023

Approximately one-half of the 34 769 cases reported from April 2021 to December 2023 were males (50.9%, 17 700/34 768) and one-fifth were aged <5 y (18%, 6276/34 768). The median age of cases was 16 (IQR 9–29) y. The number of cases reported in the IHIP increased over the years from 2021 to 2023. Among the 34 768 cases, 88% were positive for P. falciparum and 3% tested positive for mixed species.

Discussion

Our study estimated malaria incidence from the data generated from both old and new information systems for malaria surveillance. Until March 2021, it was aggregate reporting, and since April 2021, the state started to record and report the daily occurrence of confirmed cases of malaria through the IHIP. This indicator-based surveillance via the IHIP provided us with the time, place and personal data for each of the cases, leading to a detailed descriptive epidemiological analysis.

Incidence of malaria and its decline during the COVID-19 pandemic

The estimated incidence of malaria as API per 1000 population declined from 2015 to 2021, followed by an increase in 2023. The decrease in API during 2020 and 2021 is probably due to decreased reporting resulting from the coronavirus disease 2019 (COVID-19) pandemic and the implementation of a new information system (i.e. the IHIP) for reporting cases.^6,7 India reported a 45% decline in malaria cases in 2020 compared with 2019.⁸ The pattern was similar to other vector-borne diseases such as dengue.⁹ Prioritization of healthcare services towards COVID-19 during the pandemic, misdiagnosis of malaria, the lack of reporting and a lag in learning new information systems were probable reasons for the decline in incidence.^6,10,11 The decline from 2015 to 2021 is consistent with Assam, another high malaria burden state in India, where the API declined from 2.6 in 2018 to 0.01 in 2021.¹² Malaria-endemic countries have documented that malaria control activities, including insecticide-treated bed net distribution and the availability of antimalarial drugs, were hampered during the COVID-19 pandemic.¹³

In addition, the pattern of change in malaria incidence is consistent with the ABER over the years. The ABER was documented to be <10% in all reported years. The decline in cases from 2015 to 2020 is probably due to reduced testing. From 2015 to 2019, Chhattisgarh showed a decrease in TPR, dropping from 6.2% in 2015 to 2.7% in 2019. However, during 2020 and 2021, the TPR increased to 3.8% and 3.7%, respectively, despite a sharp decrease in the total number of people being tested. This decrease in testing coincided with the COVID-19 pandemic, which likely disrupted routine malaria services, reduced access to diagnostics and redirected the focus of the health system. Although fewer people were tested, the proportion of those who tested positive remained consistent, suggesting that testing during this period may have been more targeted, focusing on symptomatic or high-risk individuals rather than widespread community screening. During 2022 and 2023, testing coverage improved. However, the TPR also increased to 4.7% in 2022 and to 5.7% in 2023, almost returning to 2015 levels. This increase may indicate a resurgence in malaria transmission, possibly due to gaps created during the COVID-19 pandemic or a decline in preventive activities. Alternatively, it may reflect more focused testing among symptomatic individuals, but the increase is still a point of concern. The rising TPR in recent years underscores the need to re-evaluate malaria control strategies, reinforce surveillance and ensure that testing and treatment services are widely accessible to prevent further escalation.

In our study, the rise in cases during July–August is probably due to the monsoon seasonal pattern. This season is characterized by optimal rainfall, which promotes vector breeding and leads to an increase in malaria cases.¹² The link was established between the increase in cases and seasonal patterns in another similar setting, in Assam, India. A similar study in Northeast India found that high rainfall was the main reason for the rapid spread of malaria.¹⁴ A positive correlation was observed between malaria cases and rainfall in Odisha and Rajasthan, India.^15,16 Because many cases occur in the third quarter of each year, strengthening malaria control efforts (such as intensive awareness campaigns) during May–June is effective.

We observed higher incidence in southern Chhattisgarh, which has a high tribal and endemic pattern. In a similar tribal setting in India, 9% tested positive for malaria in the community survey. Approximately 80% of cases were from high endemic areas.¹⁷ One study projected the annual malaria case data reported under the National Center for Vector Borne Diseases Control, Chhattisgarh, India, to estimate the elimination progress of malaria. The data revealed that malaria data of the Bastar district and three other districts (Dantewada, Bijapur and Narayanpur) under the Bastar division were projected to fall short of the zero case target by 2030.¹⁸ This could be mainly attributed to the heavily forested areas inhabited by predominantly native tribal populations, which have remained endemic for malaria since the inception of the national malaria control program. In addition, the higher burden of asymptomatic malaria cases (>20%) further leads to persistent transmission of malaria in this area.¹⁰ The Southern region reported an increased number of cases, probably due to the implementation of a test-treat-track strategy by the state government to capture missed cases through a campaign called ‘Malaria Mukt Bastar’. The campaign focuses on screening the hard-to-reach population in a phased manner from 2020.^19,20

We observed an inclining trend in the proportion of P. falciparum cases reported over the years in Chhattisgarh. A global spatial modeling study revealed that the malaria burden declined from 2000 to 2017.²¹ Although the number of P. falciparum cases declined in our study, the proportion of P. falciparum cases among the total malaria cases has remained >85% since 2020. This suggests that the susceptibility of P. falciparum is higher in Chhattisgarh and has remained persistent over the years, contributing to continuous transmission. Odisha, a neighboring state of Chhattisgarh, documented 88% of malaria cases due to P. falciparum species.¹⁵ An increase in the P. falciparum proportion could increase the incidence of complicated malaria, mainly affecting children and vulnerable adults. Health systems need to strengthen the treatment centers with drugs, logistics and trained manpower, especially in these regions.

In our analysis, approximately one-half of cases were aged <15 y. Ahmed et al.¹² conducted a study in Assam, India, which revealed that 16% were aged <5 y and that 29% were aged 5–14 y among the 2130 cases. In a mass screening survey conducted in Northeast India in 2017, the burden of malaria declined with an increase in age.¹⁷ The findings align with our observations and indicate that even over the years, the malaria burden remains particularly high among children and younger age groups.

Strengths and limitations

Data representing a larger population of states with reporting from different levels of institutions and case-based surveillance data over the years were observed as major strengths of our analysis. Our study had certain limitations. First, our data lack details on clinical characteristics, including comorbidities, duration of the illness and outcome of the cases. Second, clinical details of the malaria deaths were absent in our data, such as duration of hospitalization and clinical severity. We believe the incidence reported in our study was an underestimate because the data were from the selected reporting units of the program, which may lack adequate regional representation of all malaria cases that occurred during the period. Additionally, studies reported that approximately 5–10% of asymptomatic individuals tested positive for malaria in similar high-burden settings such as Odisha (18%)²² and Maharashtra (4.2%).²³ A community-based cross-sectional study conducted in Kondagaon district, Chhattisgarh, determined that the prevalence of asymptomatic malaria cases was >20%.¹⁰ Also, the sensitivity and timeliness of the reporting system in capturing the cases were unknown. Hence, the reported incidence and burden in our study could be an underestimate of the malaria burden in Chhattisgarh. Our analysis had certain limitations, such as adjusting for year and administrative districts in the GEE. However, there could have been other factors, including unknown confounders, which could have impacted the API, such as the distribution and correct usage of long-lasting insecticidal nets. However, we could not adjust for those factors as data relating to those factors were not available in the database used for the analysis.

Conclusions

We conclude that malaria incidence increased in 2023, followed by a decline in 2021 since 2015. The Bastar region of Chhattisgarh consistently documented increased incidence over the years. The cases peaked in July during the monsoon season. Annual blood examination rates were consistently <10% from 2015 to 2023. The P. falciparum strain was prevalent and increased over the years. We recommend strengthening implementation of the vector control measures during May–June, improving the testing rates by >10% as per program guidelines and health system preparedness measures to cater for P. falciparum severe malaria. Further research should be conducted to identify the reasons for the high malaria incidence in southern Chhattisgarh. Additionally, we recommend evaluating the surveillance system for malaria in Chhattisgarh.

Authors’ contributions

DKG, MK, GPK, MS and PG conceived the study; DKG, MK, GPK, DKP, JKD, KP, MR, ST, TJ, YP, AK, AR, MS and PG analyzed and interpretated the data; DKG, GPK, PG, MK and AK drafted the manuscript; DKG, PG and MK critically revised the manuscript for intellectual content. All the authors read and approved the final manuscript.

Funding

None.

Competing interests

Not declared.

Ethical approval

We obtained permission from the Chhattisgarh State Surveillance Unit to analyze the data. We abstracted the de-identified data from the IHIP. The research team did not have access to patient identification details. There was no direct involvement of patients or the public in designing the study, determining outcome measures, analyzing data or interpreting findings.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.