Impact assessment of Intensified Malaria Control Project in transitioning a high malaria-endemic district to a low-endemic district: an epidemiological aspect

Intensified Malaria Control Project (IMCP) was implemented in 2005 to control malaria in all North-Eastern and Odisha states of India. The present study aimed to investigate the impact of IMCP in reducing the malaria burden in Udalguri district, Assam state of North-East India. Malaria epidemiological data were obtained for IMCP intervention (Udalguri) and nonintervention district (West Singhbhumi, Jharkhand state). IMCP activities include introducing bi-valent rapid diagnostic kits (RDTs), Artemether-Lumefantrine drug in North-East India, long-lasting insecticidal nets (LLINs) distribution, and creating awareness programs about malaria in an intensified mode. The data revealed a significant decline in annual parasite incidence (API) from 14.94 (2005) to 2.61 (2018), -37% (95%CI: -57%, -19%, p = 001) after using LLINs in 2009 and -64% (95%CI: -116%, -14%, p = 013) after the introduction of RDTs in district Udalguri. Whereas control district showed a -28% (95%CI: -63%, 6.3%, p = 0.051) decrease in API using LLINs and a 10% (95%CI: -7.6%, 28%, p = 0.122) increase after the introduction of RDTs. Plasmodium falciparum (Pf) and P. vivax (Pv) were the major malarial parasites in Udalguri. Pv-malaria was much higher (71%) than Pf-malaria (29%) during the study period. An increasing trend of Pf cases was observed in Udalguri. Udalguri and Khoirabari BPHCs showed an overall reduction of 94% (95%CI: -143%, -45%, p = 0.001) and 84% (95%CI: -126%, -39%, p = 0.003), respectively; however, only a 10% (95%CI: -65%, -41%, p = 0.360) reduction in API was observed in Orang BPHC. An overall decrease in malaria indicates the effective implementation of vector and disease control strategies in the Udalguri district.

Climate zones are a key component of the heterogeneous presentation of malaria and should be added as a malariometric for the planning of malaria elimination

Malaria is a climate-sensitive disease and different climatic conditions affect the propagation of malaria vectors thereby influencing malaria incidence. The present study was undertaken to delineate malaria distribution across different climate types and sub-types in India and assess its significance as a malariometric in the ongoing elimination activities. All Indian districts were classified into three major climatic zones (Tropical, Temperate, and others (Arid, Cold, and Polar) based on the Köppen-Geiger climate classification system. The Annual Parasite Incidence (API) of malaria was analyzed in these climatic zones using the Kruskal Wallis test, and a post hoc comparison was done using the rank-sum test with an adjusted p-value for the level of significance. Further logistic regression was used to investigate the association of these climatic zones with high malaria incidence (i.e., API>1). The majority of Indian districts fall in Temperate (N = 270/692 (39.0%)) and Tropical (N = 260/692 (37.6%)) regions, followed by Arid (N = 140/692 (20.2%)), Polar (N = 13/692 (1.9%)) and Cold (N = 9/692 (1.3%)) regions. Three climate zones: Arid, Polar, and Cold were similar in terms of malaria incidence over the years and thus were grouped into one. It was found that the tropical and temperate zones display a significantly higher burden of malaria as compared to others for the studied years (2016-2021). Future projections of climate suggest a significant expansion of tropical monsoon climate towards central and northern India, along with a growing footprint of tropical wet savannah climate in the northeast of India by 2100, which could increase the risk of malaria transmission in these regions. The heterogeneous climatic zones of India play an important role in malaria transmission and can be used as a malariometric for the stratification of districts destined for malaria elimination.

Linkages between malaria and malnutrition in co-endemic regions of India

INTRODUCTION

Malaria and malnutrition are key public health challenges in India. However, the relationship between them is poorly understood. Here, we aimed to elucidate the potential interactions between the two health conditions by identifying the areas of their spatial overlap.

METHODS

We have analysed the district-wise undernutrition and malaria data of 638 districts of India across 28 states and 8 union territories. Data on malnutrition parameters viz. stunting, wasting, underweight and anaemia, sourced from the fourth National Family Health Survey (2015-2016), and malaria Annual Parasite Index (API) data of the same year (i.e, 2015), sourced from National Center of Vector Borne Diseases Control were analysed using local Moran's I Index and logistic regression.

RESULTS

Among all the malnutrition parameters, we found underweight in children and anaemia in men to co-occur with malaria in the districts of Chhattisgarh, Jharkhand, Madhya Pradesh and Odisha. Further, districts with more than 36% underweight children (OR (95% CI): 2.31 (1.53 to 3.48)) and/or more than 23.6% male population with anaemia (OR (95% CI): 2.06 (1.37 to 3.11)) had higher odds of being malaria endemic districts (ie, Annual Parasite Index >1).

CONCLUSION

Malaria and malnutrition co-occur in the malaria-endemic parts of India. The high prevalence of undernutrition in children and anaemia among men may contribute to malaria endemicity in a particular region. Therefore, future research should be prioritised to generate data on the individual level. Further, malaria control interventions could be tailored to integrate nutrition programmes to disrupt indigenous malaria transmission in endemic districts.

Tracking district-level performance in the context of achieving zero indigenous case status by 2027

India has committed to zero indigenous malaria cases by 2027 and elimination by 2030. Of 28 states and 8 union territories of India, eleven states were targeted to reach the elimination phase by 2020. However, state-level epidemiology indicates that several states of India may not be on the optimum track, and few goals set in National Framework for Malaria Elimination (NFME) for 2020 remain to be addressed. Therefore, tracking the current progress of malaria elimination in India at the district level, and identifying districts that are off track is important in understanding possible shortfalls to malaria elimination. Annual malaria case data from 2017-20 of 686 districts of India were obtained from the National Center for Vector-Borne Diseases Control (NCVBDC) and analysed to evaluate the performance of districts to achieve zero case status by 2027. A district's performance was evaluated by calculating the annual percentage change in the total number of malaria cases for the years 2018, 2019 and 2020 considering the previous year as a base year. The mean, median and maximum of these annual changes were then used to project the number of malaria cases in 2027. Based on these, districts were classified into four groups: 1) districts that are expected to reach zero case status by 2027, 2) districts that would achieve zero case status between 2028 and 2030, 3) districts that would arrive at zero case status after 2030, and 4) districts where malaria cases are on the rise. Analysis suggest, a cohort of fifteen districts require urgent modification or improvement in their malaria control strategies by identifying foci of infection and customizing interventions. They may also require new interventional tools that are being developed recently so that malaria case reduction over the years may be increased.

An investigation of the efficacy of different statistical models in malaria forecasting in the semi-arid regions of Gujarat, India

BACKGROUND & OBJECTIVES

Robust forecasting of malaria cases is desirable as we are approaching towards malaria elimination in India. Methods enabling robust forecasting and timely case detection in unstable transmission areas are the need of the hour.

METHODS

Forecasting efficacy of the eight most prominent statistical models that are based on three statistical methods: Generalized linear model (Model A and Model B), Smoothing method (Model C), and SARIMA (Model D to model H) were compared using last twelve years (2008-19) monthly malaria data of two districts (Kheda and Anand) of Gujarat state of India.

RESULTS

The SARIMA Model F was found the most appropriate when forecasted for 2017 and 2018 using model-building data sets 1 and 2, respectively, for both the districts: Kheda and Anand. Model H followed by model C were the two models found appropriate in terms of point estimates for 2019. Still, we regretted these two because confidence intervals from these models are wider that they do not have any forecasting utility. Model F is the third one in terms of point prediction but gives a relatively better confidence interval. Therefore, model F was considered the most appropriate for the year 2019 for both districts.

INTERPRETATION & CONCLUSION

Model F was found relatively more appropriate than others and can be used to forecast malaria cases in both districts.

Epidemiology of malaria and anemia in high and low malaria-endemic North-Eastern districts of India

Anemia and malaria are the two major public health problems that lead to substantial morbidity and mortality. Malaria infection destroys erythrocytes, resulting in low hemoglobin (Hb) levels known as anemia. Here we report the determinants of anemia in high and low malaria-endemic areas that would help understand which parasite densities, age, and gender-associated low Hb levels. Therefore, a cross-sectional mass survey (n = 8,233) was conducted to screen anemia and malaria in high and low malaria-endemic districts (HMED and LMED) of North-East India. Axillary body temperature was measured using a digital thermometer. The prevalence of anemia was found to be 55.3% (4,547/8,233), of which 45.1% had mild (2,049/4,547), 52.1% moderate (2,367/4,547) and 2.9% had severe anemia (131/4,547). Among anemic, 70.8% (3,219/4,547) resided in LMED and the rest in HMED. The median age of the anemic population was 12 years (IQR: 7–30). Overall, malaria positivity was 8.9% (734/8,233), of which HMED shared 79.6% (584/734) and LMED 20.4% (150/734) malaria burden. The village-wise malaria frequency was concordant to asymptomatic malaria (10–20%), which showed that apparently all of the malaria cases were asymptomatic in HMED. LMED population had significantly lower Hb than HMED [standardized beta (β) = −0.067, p < 0.0001] and low-density Plasmodium infections had higher Hb levels than high-density infections (β = 0.113; p = 0.031). Women of reproductive age had higher odds for malaria (OR: 1.42; 95% CI: 1.00–2.05; p = 0.04). Females (β = −0.193; p < 0.0001) and febrile individuals (β = −0.029; p = 0.008) have shown lower Hb levels, but malaria positivity did not show any effect on Hb. Young children and women of reproductive age are prone to anemia and malaria. Although there was no relation between malaria with the occurrence of anemia, we found low-density Plasmodium infections, female gender, and LMED were potential determinants of Hb.

Moderate Rainfall and High Humidity During the Monsoon Season, Negligence in Using Malaria Protection Methods and High Proportion of Mild Symptomatic Patients Were the Driving Forces for Upsurge of Malaria Cases in 2018 Among Tea Tribe Populations in Endemic Dolonibasti Health Sub-center, Udalguri District, Assam State, North-East India

Malaria elimination is a global priority, which India has also adopted as a target. Despite the malaria control efforts like long-lasting insecticidal nets distribution, rounds of indoor residual spray, the introduction of bi-valent rapid diagnostic tests and artemisinin combination therapy, malaria remained consistent in Dolonibasti sub-center of Orang block primary health center (BPHC) under the district Udalguri, Assam state followed by abrupt rise in cases in 2018. Therefore, we aimed to investigate the factors driving the malaria transmission in the outbreak area of Dolonibasti sub-center. Malaria epidemiological data (2008–2018) of Udalguri district and Orang BPHC was collected. The annual (2011-2018) and monthly (2013–2018) malaria and meteorological data of Dolonibasti sub-center was collected. An entomological survey, Knowledge, Attitude and Practices study among malaria cases (n = 120) from Dolonibasti was conducted. In 2018, 26.1 % (2136/ 8188) of the population of Dolonibasti were found to be malaria positive, of which 55% were adults (n = 1176). Majority of cases were from tea tribe populations (90%), either asymptomatic or with fever only, 67.5 % (81/120) had experienced malaria infection during past years. The outbreak was characterized by a strong increase in cases in June 2018, high proportion of slide falciparum rate of 26.1% (other years average, 15.8%) and high proportion of P. falciparum of 81.2 % (other years average, 84.3%). Anopheles minimus s.l. was the major vector with 28.6% positivity and high larval density in paddy fields/ drainage area. Annual relative humidity was associated with rise in malaria cases, annual parasite incidence (r_s = 0.69, 90%CI; p = 0.06) and slide positivity rate (r_s = 0.83, 95%CI; p = 0.01). Older people were less educated (r_s = −0.66; p < 0.001), had lesser knowledge about malaria cause (r_s = −0.42; χ²=21.80; p < 0.001) and prevention (r_s = −0.18; p = 0.04). Malaria control practices were followed by those having knowledge about cause of malaria (r_s = 0.36; χ² = 13.50; p < 0.001) and prevention (r_s = 0.40; χ² = 17.71; p < 0.001). Altogether, 84.6% (44/52) of the respondents did not use protective measures. We described a sudden increase in malaria incidence in a rural, predominantly tea tribe population group with high illiteracy rate and ignorance on protective measures against malaria. More efforts that are concerted needed to educate the community about malaria control practices.

Distribution Expansion of Dengue Vectors and Climate Change in India

India has witnessed a five-fold increase in dengue incidence in the past decade. However, the nation-wide distribution of dengue vectors, and the impacts of climate change are not known. In this study, species distribution modeling was used to predict the baseline and future distribution of Aedine vectors in India on the basis of biologically relevant climatic indicators. Known occurrences of Aedes aegypti and Aedes albopictus were obtained from the Global Biodiversity Information Facility database and previous literature. Bio-climatic variables were used as the potential predictors of vector distribution. After eliminating collinear and low contributing predictors, the baseline and future prevalence of Aedes aegypti and Aedes albopictus was determined, under three Representative Concentration Pathway scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), using the MaxEnt species distribution model. Aedes aegypti was found prevalent in most parts of the southern peninsula, the eastern coastline, north eastern states and the northern plains. In contrast, Aedes albopictus has localized distribution along the eastern and western coastlines, north eastern states and in the lower Himalayas. Under future scenarios of climate change, Aedes aegypti is projected to expand into unsuitable regions of the Thar desert, whereas Aedes albopictus is projected to expand to the upper and trans Himalaya regions of the north. Overall, the results provide a reliable assessment of vectors prevalence in most parts of the country that can be used to guide surveillance efforts, despite minor disagreements with dengue incidence in Rajasthan and the north east, possibly due to behavioral practices and sampling efforts.

Prevalence of sibling-species of Anopheles (Cellia) fluviatilis complex in Himachal Pradesh, India

BACKGROUND & OBJECTIVES

Malaria is one of the most infectious and life-threatening vector borne disease in the tropics. Climate change can significantly influence malaria epidemiology and expansion of malaria vectors to hilly regions of Himachal Pradesh in India, hitherto considered areas of low transmission. Entomological surveillance in Kangra district of Himachal Pradesh revealed high density of a proven efficient vector of malaria, Anopheles fluviatilis, but transmission intensity of malaria was found very low. It was therefore considered prudent to investigate the sibling-species composition of An. fluviatilis complex in Kangra valley to ascertain their role in transmission of malaria.

METHODS

The study was undertaken in six villages in Kangra district of Himachal Pradesh, India. A total of 4446 mosquitoes were collected during the one-year study period (2018) and processed in pools of ten for molecular characterization. DNA extraction and multiplex PCR was performed on 900 An. fluviatilis mosquitoes for differentiation of sibling-species. ELISA was used to detect Plasmodium falciparum and Plasmodium vivax circumsporozoite proteins in 3790 An. fluviatilis samples.

RESULTS

Among prevalent mosquito species, An. fluviatilis was the predominant species constituting 69.5% of total mosquito collection. Sibling-species U was found in 92.22% and species T in 7.78% samples assayed. ELISA confirmed the absence of evidence of malaria parasite in any of the An. fluviatilis mosquitoes screened. Based on the difference in the sequences of conserved regions of the 28SrDNA, sibling-species U was confirmed as prevalent in the study villages.

INTERPRETATION & CONCLUSION

Study revealed that in Kangra district, An. fluviatilis sibling-species U is predominant followed by species T, and both are non-vectors. The absence of malaria parasite and zoophagic nature of An. fluviatilis established through blood meal analysis, confirmed that both U and T are non-vector sibling-species.