Journal of Vector Borne Diseases

: 2020  |  Volume : 57  |  Issue : 1  |  Page : 31--36

Cost of care and its impact on households due to lymphatic filariasis: Analysis of a national sample survey in India

Jaya Prasad Tripathy1, BM Prasad2,  
1 Department of Community Medicine, All India Institute of Medical Sciences, Nagpur, India
2 International Union against Tuberculosis and Lung Disease, The Union Southeast Asia Office, New Delhi, India

Correspondence Address:
Dr Jaya Prasad Tripathy
Assistant Professor, Department of Community Medicine, All India Institute of Medical Sciences, Nagpur


Background and objectives: India is an endemic country for lymphatic filariasis (LF). There are no current estimates of the expenditure being borne by LF patients in case of outpatient care or hospitalisation and its impact on households. This study aimed to estimate the household out-of-pocket (OOP) expenditure due to hospitalization or outpatient care as a result of LF in India. Methods: Secondary analysis of nationally representative data for India collected by the National Sample Survey Organization in 2014 was performed, reporting on health service utilization and health care related OOP expenditure by income quintiles and by type of health facility (public or private). Results: The median household OOP expenditure from hospitalization and outpatient care due to LF was US$ 178 and US$ 04, respectively; and was more than two times higher among the richest group compared to the poorest. There was a significantly higher proportion of households affected by catastrophic costs among the rich (30%) compared to the poor households (18%) due to hospitalization. Median private sector OOP hospitalization expenditure was nearly four times higher than the public sector. Less than one-fourth of outpatient visits (22%) were in the public sector. The median expenditure on medicines and indirect cost were US$ 32 (IQR: 17–84) and US$ 23 (IQR: 9–59), respectively in case of hospitalization due to LF; while in case of outpatient care these were US$ 1.5 (IQR: 0–5.8) and US$ 1.5 (IQR: 0–4), respectively. Interpretation & conclusion: Households with LF incur huge cost of patient care, particularly those in the lowest income group and those seeking care in the private sector.

How to cite this article:
Tripathy JP, Prasad B M. Cost of care and its impact on households due to lymphatic filariasis: Analysis of a national sample survey in India.J Vector Borne Dis 2020;57:31-36

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Tripathy JP, Prasad B M. Cost of care and its impact on households due to lymphatic filariasis: Analysis of a national sample survey in India. J Vector Borne Dis [serial online] 2020 [cited 2021 Apr 19 ];57:31-36
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Lymphatic filariasis (LF) is a vector-borne neglected tropical disease targeted for elimination as a public health problem. An estimated 1.34 billion live in filarial endemic areas and are, therefore, at risk of infection[1]. Approximately, 65% of those at risk reside in WHO’s South-East Asia Region (SEAR)[1].

Since 2000, a cumulative total of 6.7 billion treatments have been delivered to >850 million people at least once[2]. It has been previously reported in 2016 that the coverage of the total population requiring mass drug administration (MDA) was 57.9% with 495.6 million people treated in 40 reporting countries[2]. It is estimated that after 13 yr of the MDA programme, there are still an estimated 68 million LF cases that include 36.45 million microfilaria carriers, 19.43 million hydrocele cases and 16.68 million lymphoedema cases[3]. Besides mortality and morbidity due to LF, reduced productivity experienced by LF patients results in hundreds of millions of dollars in economic losses each year.

The Global Programme to Eliminate Lymphatic Filariasis (GPELF) embodies two “pillars”: stopping new infections by the year 2020 and managing morbidity and preventing disability for people already infected[1]. Of the 73 endemic countries, 62 had initiated MDA[3],[4] for elimination of new infections as of 2014. As of 2015, 45 countries were considered “on track” to achieve elimination targets[3] by 2020.

India is one of the nine filarial endemic countries in the SEAR with 40% of the global filariasis burden and 50% of the global population at risk of infection which is nearly 600 million people[4]. The cost of care of patients with LF is significant as it is evident from previous studies. However, all these studies were conducted in rural communities of specific geographical locations more than two decades back. There are no current estimates of the expenditure being borne by patients with LF in case of outpatient care or hospitalisation and its impact on households.

The National Sample Survey Organisation (NSSO) in India conducts regular, nationally representative household surveys collecting household socioeconomic information. In its 71st survey, NSSO collected household level data on health care expenditure. This provides an opportunity to investigate household expenditures related to LF. Using the 2014 NSSO data, this study aimed to estimate the median out-of-pocket (OOP) expenditure and the proportion of families affected by catastrophic costs due to hospitalization or outpatient visits resulting from LF.

 Material & Methods

Study design

This is a secondary data analysis of a large representative nationwide survey data collected by the NSSO, India. Similar methodology has been used by the authors in a previous study using this survey dataset[5].

Data source

NSSO is a national organisation which was established in 1950 to regularly conduct nationwide surveys and provide useful statistics related to socioeconomic status of households, demography, health, industries, agriculture, consumer expenditure, etc. The 71st round of survey was carried out during January–June 2014. It collected household level data on health care utilization and expenditure for various ailments. A multistage stratified sampling design was adopted. The first stage units were the census villages in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. For the rural sector, the list of 2011 census villages constituted the sampling frame. For the urban sector, the latest updated list of UFS blocks (phase 2007–12) was considered as the sampling frame. The ultimate stage units (USU) were households in both the sectors. The total number of sample FSUs were allocated to the States and UTs in proportion to population as per Census 2011. A minimum of 16 FSUs (minimum 8 each for rural and urban sector separately) were allocated to each State/ UT.


Stratum has been formed at district level. Within each district of a State/UT, generally speaking, two basic strata have been formed: (i) rural stratum comprising of all rural areas of the district; and (ii) urban stratum comprising of all the urban areas of the district. Within each sector of a State/ UT, the respective sample size has been allocated to the different strata in proportion to the population as per Census 2011.

Selection of FSUs

For the rural sector, from each stratum/substratum, required number of sample villages has been selected by Probability Proportional to Size With Replacement (PPSWR), size being the population of the village as per Census 2011. For the urban sector, from each stratum/ substratum, FSUs have been selected by PPSWR, size being the number of households of the UFS blocks.

Selection of households

In each FSU, three Second Stage Sampling (SSS) units were created comprising of: (i) households having at least one child of age less than 1 yr; (ii) from the remaining, households with at least one member (including deceased former member) hospitalized during last 365 days; and (iii) other households. From each SSS, sample households were selected by simple random sampling without replacement. A total of 4577 villages and 3720 urban blocks were surveyed from which 36,480 and 29,452 households were sampled in rural and urban areas, respectively. A total of 333,104 persons were interviewed. The detailed methodology can be found in the survey report[6].

A subset of the survey data reporting hospitalization (in the last 365 days preceding the survey) and outpatient care (in the last 15 days prior to the survey) for LF was selected for analysis. In the survey, LF was coded as 06 under the section “Infections”. Disease conditions in the household survey were self-reported. However, self-report was cross-checked by referring to OPD slips, hospital discharge papers etc. wherever possible.

The household members were asked whether they received any OPD care in the last 15 days or hospitalized in the last 365 days due to any ailment, LF being one of them. If yes, then OOP expenditure related to drugs; diagnostic tests (including ECG, X-ray, pathological tests, etc); professional fees for doctors; other medical expenses (bed charges, physiotherapy, personal medical appliances, blood, oxygen, attendant charges, etc); and other indirect costs (transport, food and lodging for the patient and other accompanying persons) were recorded. The expenditure figures were based on self-report by the participants; however, efforts were made to validate the figures by referring to payment receipts, prescriptions or bills wherever available. Data were also collected on type of facility (public or private) accessed for medical care.

The recall periods for assessing expenditure due to hospitalization and outpatient care were 365 days and 15 days, respectively. Household consumption expenditure in the last one month was also recorded (as a proxy for household income). The OOP expenditure incurred as a result of hospitalization amounting to more than 30 per cent of annual household consumption expenditure was termed as ‘catastrophic’[7],[8],[9]. Distress financing is defined as borrowing money from relatives/friends, taking out loans from banks/other lenders or selling assets to cope with OOP expenditure on medical treatment due to any illness. Household is defined as a group of persons normally living together and taking food from a common kitchen.

Data analysis

Data were imported into SPSS version 17.0 for analysis. The study population was divided into tertiles based on monthly per capita consumption expenditure (MPCE). The household MPCE limits (in US$) for three tertiles were as follows: first (7–17), second (18–25) and third (26–65). Median values/percentages for all indicators were presented across each of the three MPCE tertiles and type of health facility (public and private). Median household expenditure was estimated for those who reported hospitalization or outpatient care due to LF. The survey reports expenditure per episode of hospitalization or outpatient visit. However, aggregate function (using household ID as the key) in SPSS was used to derive the total household healthcare expenditure due to LF. Thus, the unit of analysis here is the household. Since it is a multistage stratified random survey, estimates were derived by applying sampling weights given by the NSSO.

Ethical statement

The source of data for the study was a national survey conducted by the Government of India and the dataset is available in public domain. The Ethics Advisory Group of International Union against Tuberculosis and Lung Disease, Paris, France, waived off the need for ethics clearance in this study.


Sociodemographic and medical care-related characteristics

A total of 38 episodes of hospitalization due to LF in the last one year were reported. Nearly two-third of those hospitalized were aged 45 yr and above (n = 26, 68%) and majority of them were males (n = 32, 84%). Half of them (n = 19, 50%) were hospitalized in the private sector. One-third of those hospitalized (n = 13, 34%) stayed in the hospital for more than seven days. A total of 36 episodes of outpatient care for LF were reported in the last 15 days. The majority were males (n = 24, 67%), more than half (n = 20, 56%) were aged 45 yr and above and 72% (n = 26) were treated in the private sector [Table 1]{Table 1}

In-patient care expenditure

The median household OOP expenditure from hospitalization due to LF was 178 US$, and was more than two times higher among the rich group (US$ 250) compared to the poor household group (US$ 108). Further analysis revealed that catastrophic expenditure was higher among the rich group (30%) compared to the poor households (18%). Majority of the households in the poor quintile (73%) utilized public sector for hospitalization compared to the rich households (27%). Equity ratios showed that hospitalization expenditure (0.43), catastrophic expenditure (0.6) and utilization of public health facility (2.7) were significantly different across wealth quintiles, thereby indicating gross inequity.

Median private sector OOP hospitalization expenditure (US$ 221) was nearly 4 times higher than the public sector (US$ 60). A higher proportion of families was found to be affected by catastrophic costs when care was sought from a private health facility (30%) compared to a public facility (14%). In more than one-fifth of the hospitalization (23%), patient costs were covered through borrowing or sale of assets. This was similar in both the first and the third wealth tertiles (20%), but higher among those who received care from the private sector [Table 2]. The median expenditure on medicines was US$ 32 (IQR: 17–84) and on indirect cost was US$ 23 (IQR: 9–59) in case of hospitalization due to LF [Figure 1].{Figure 1}{Table 2}

Outpatient expenditure

The median expenditure per episode of outpatient visit due to LF was US$ 4. Overall, less than one-fourth of outpatient visits (22%) were in the public sector. Public sector utilization by the poor household group (25%) was almost 2.5 times higher compared to the rich household group (10%). Median outpatient OOP expenditure due to LF was US$ 6 in the private sector and US$ 3 in the public sector [Table 3]. The median expenditure on medicines was US$1.5 (IQR: 0–5.8) and on indirect cost was US$ 1.5 (IQR: 0–4) in case of outpatient care due to LF [Figure 2].{Figure 2}{Table 3}


The study highlights high household OOP expenditure from hospitalization and outpatient care and higher instances of catastrophic expenditure due to hospitalization among the rich household group and those seeking care in the private sector. Poor public sector utilization was also a key concern that emerged. Previous studies have also shown that LF exerts a considerable economic burden on affected individuals[10],[11],[12]. However, due to lack of recent study, comparison of cost figures will not be fair due to different time periods. Despite this, it is clear from the literature that the economic burden of LF care on families is hugely similar to the findings of the present study. The cost estimates in this study will be useful in revising the Rashtriya Swasthya Bima Yojana (RSBY) rates for expenses due to filariasis related hospitalizations.

The private sector takes the lion share in the provision of health services for hospitalizations and outpatient care associated with LF. The median OOP hospitalization expenditure in private sector was nearly four times higher than the public sector. In the last decade, there has been a significant rise in private sector expenditure on health care. This reflects the inability of the government to regulate the private sector and effectively engage them in equitable delivery of health care.

Overall, there was poor utilization of public sector, although encouragingly, there was a higher rate of public sector utilization among the poorer quintiles. Similar findings have been shown in other studies in India[5],[9]. Despite RSBY scheme and free provision of health services in the public sector, a person pays on an average US$ 60 for a single episode of hospitalization due to LF. This is probably due to the costs of medicines and other medical supplies as shown in this study. Thus, to increase access and affordability of health care in the public sector, promotion of generic medicines, greater availability of medicines and other supplies and subsidization for the poor population quintiles is required.

There are a few limitations in this study. First, this study underestimates the costs of LF morbidity in many ways. We did not include any account of other externalities of LF morbidity such as the costs due to loss of wages for both the patient and the family care givers and the impact on child education and nutrition which could affect the child’s future. This study measures only the economic costs borne directly by the patient and we exclude costs to others, including society as a whole or government. Second, OOP expenditure was based on recall of patients and were self-reported which might lead to recall bias and self-reporting bias. Third, OOP expenditure as a proportion of annual household expenditure and cutoffs used for catastrophic expenditure has been well-debated in the literature. Fourth, there was no information on the type and severity of the disease. Fifth, only those who accessed care for LF were included in the study leaving behind those who did not access any care, which might overestimate the study findings.

Despite these limitations, we feel that the study results are alarming and need urgent attention in terms of providing more financial security, especially to the poor through direct cash transfer or insurance schemes.


The OOP expenditure associated with LF care is significant, especially among the poor in India. Utilization of public health facilities results in lower OOP expenses than the use of private facilities which warrants strengthening of public sector facilities for better risk protection.


We thank the Department for International Development (DFID), United Kingdom, for funding the Global Operational Research Fellowship Programme at the International Union against Tuberculosis and Lung Disease (The Union), Paris, France in which Jaya Prasad Tripathy worked as a Senior Operational Research Fellow previously.

Conflict of interest

The authors declare that there are no competing interests.


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