4.1 Demographic Information and Dynamics of KFD-related Awareness
Over two-thirds of the sampled respondents interviewed (68.6%) were male largely, which is reflective of the social and occupational context (Table 1). Nearly 75% respondents are of working age (i.e. 15–64 years cluster) with mean ages of 57.6 and 47.1 in Shimoga and Wayanad respectively. On the social stratification scale, the overwhelming majority of respondents (84.2%) reported belonging to a lower caste (i.e. scheduled tribe, scheduled caste and other backward classes (OBC) as per statutory classification of caste groups in India). Of the 157 respondents interviewed in Shimoga, about 96% identified themselves as belonging to a lower caste relative to the 58.3% in Wayanad. A majority of respondents (70.3%) reported some form of formal schooling, with a relatively even distribution across the two study areas. In Shimoga for instance, whereas 30.6% of respondents claimed they had no formal education, 26.5% attained secondary level and 7% tertiary education respectively. In Wayanad, 28% had no formal education, 30% completed secondary level and 4% tertiary education respectively. The fairly low educational attainment (8% of total sample completed higher secondary) in the surveyed communities across the two study regions could have negative implications, in terms of disease literacy by constraining access to formal sources of disease information such as newspapers, internet and information leaflets. Concerning income status, the overall results suggest that a significant proportion of surveyed households in Shimoga (88.5%) and Wayanad (63.9%) were classed as living ‘below poverty line6’, implying that they earned less than Rs. 32 (£0.35) a day, as per the revised Government of India poverty index [43]. Within this context, agriculture constituted the primary source of employment, with over half of surveyed households (56.8%) engaged in agriculture. Further disaggregation by study area revealed significant regional differences in terms of non-agriculture based employment, as nearly half (48.6%) of surveyed households in Wayanad were engaged in other primary livelihood activities as against just 9.6% of households in Shimoga within the same category (χ2 value 44.12, p ≤ 0.05). This highlights relative regional differences in socio-economic positions with significant implications for zoonotic disease vulnerability, local disease control strategies and pathways to adaptation available to individuals and households.
Table 1
The demographic characteristics of respondents by study region
Socioeconomic characteristics
|
Study sites
|
Full sample (N = 229)
|
Shimoga (N = 157)
|
Wayanad (N = 72)
|
Gender Household Head
|
|
|
|
Female
|
39 (24.8%)
|
33 (45.8%)
|
72 (31.4%)
|
Male
|
118 (75.2%)
|
39 (54.2%)
|
157 (68.6%)
|
Age Classification
|
|
|
|
Aged 15–24 years
|
1 (0.6%)
|
1 (1.4%)
|
2 (0.9%)
|
Aged 25–64 years
|
102 (65%)
|
67 (93.1%)
|
169 (73.8%)
|
Aged > 65 years (the elderly)
|
54 (34.4%)
|
4 (5.6%)
|
58 (25.3%)
|
Social Stratification (Caste)
|
|
|
|
Scheduled caste
|
8 (5.1%)
|
3 (4.2%)
|
11 (4.8%)
|
Scheduled tribe
|
26 (16.5%)
|
22 (30.5%)
|
48 (20.9%)
|
Other backward caste
|
117 (74.5%)b
|
17(23.6%)b
|
134 (58.5%)
|
Other (Upper caste)
|
6 (3.8%)
|
30 (41.7%)
|
36 (15.7%)
|
Educational Level
|
|
|
|
No formal education
|
48 (30.6%)
|
20 (28%)
|
68 (29.7%)
|
Completed primary level education
|
36 (23%)
|
20 (28%)
|
56 (25%)
|
Completed middle level education
|
20 (12.7%)
|
5 (7%)
|
25 (11%)
|
Completed matriculation/secondary level
|
33 (21%)
|
12 (16%)
|
45 (20%)
|
Higher secondary/ Pre-university
|
9 (5.7%)
|
10 (14%)
|
19 (8%)
|
Technical diploma
|
-
|
2 (3%)
|
2 (1%)
|
Tertiary education
|
11 (7%)
|
3 (4%)
|
14 (5%)
|
Religious Affiliation
|
|
|
|
Hindu
|
148 (94.3%)
|
51 (70.8%)
|
199 (86.9%)
|
Christian
|
1 (0.6%)
|
11 (15.3%)
|
12 (5.2%)
|
Muslim
|
8 (5.1%)
|
10 (13.9%)
|
18 (7.9%)
|
Poverty Status
|
|
|
|
Below poverty line (BPL)
|
139 (88.5%)
|
46 (63.9%)
|
185 (80.8%)
|
Above poverty line (APL)
|
18 (11.5%)
|
26 (36.1%)
|
44 (19.2%)
|
Primary Occupation
|
|
|
|
Agriculture-based
|
106 (67.5%)
|
24 (33.3%)
|
130 (56.8%)
|
Non-agriculture based*
|
15 (9.6%)b
|
35(48.6%)b
|
50 (21.8%)
|
Unemployed
|
36 (23%)
|
13 (18.1%)
|
49 (21.4%)
|
a Significant at p ≤ 0.01; b Significant at p ≤ 0.05 |
4.2 Dynamics of awareness and perceptions relating to KFD
To afford a better understanding of the disease information and adaptive capacity nexus in the study areas, it was pertinent to assess respondents’ level of awareness and perceptions about KFD. As shown in Table 2, almost three-quarters of all respondents (n = 166) confirmed their awareness of KFD when asked whether they had heard of the disease prior to the survey, with 26.6% reporting them and/or know someone who had contracted the disease. Although most households (totalling 69%) generally reported that KFD constituted a significant health concern in their respective villages, there were marked differences in terms of the perceived level of severity and whether people are likely to contract the disease. In this regard, the overall results indicate that households have a diverging perception about KFD, ranging from worried and extremely worried (44%) to not at all worried about the disease (56%). Despite half of the households in Wayanad expressing worry about KFD, an even lesser proportion (40.3%) perceived the likelihood of people contracting it. By contrast, the Shimoga data indicate that despite a majority of households (59%) not being worried about KFD, a fairly high percentage of respondents (55%, n = 86) expressed the likelihood of people contracting it. A further disaggregated analysis revealed statistically significant difference between prior experience of KFD (contracting or knowing someone with KFD) and feeling worried about contracting same, particularly in Shimoga. For example, the overall results indicate that as many respondents who had prior experience with KFD in Shimoga (63.2%, 24/38) also reported being worried about contracting it (χ2 value 8.02, p ≤ 0.05). A similar pattern is portrayed in the Wayanad data but is not statistically significant.
Table 2
Awareness and perceptions about KFD by study area
Categories
|
Study Regions
|
Full sample
(N = 229)
|
Shimoga (n = 157)
|
Wayanad (n = 72)
|
Past history with KFD
|
|
|
|
Have ever had/contracted KFD
|
10 (6%)
|
7 (10%)
|
17 (7%)
|
Know someone with KFD
|
28 (18%)
|
16 (22%)
|
44 (19%)
|
Heard of KFD/ Monkey fever
|
119 (75.8%)
|
47 (65.3%)
|
166 (72.5%)
|
Vaccinated against KFD
|
93 (59.2%)
|
14 (19.4%)
|
107 (46.7%)
|
Vaccination (% who have taken the vaccine once)
|
32 (34.4%)
|
3 (21.4%)
|
35 (32.7%)
|
Vaccination (% who have taken the vaccine twice)
|
10 (10.8%)
|
7 (50.0%)
|
17 (15.9%)
|
Vaccination (% who have taken the vaccine thrice)
|
43 (46.2%)
|
2 (14.3%)
|
45 (42.1%)
|
Vaccination (% who have taken the vaccine four times)
|
8 (8.6%)
|
1 (7.1%)
|
9 (8.4%)
|
Awareness of KFD
|
|
|
|
Exposure (awareness of the likelihood of people to contract KFD)
|
86 (54.8%)
|
29 (40.3%)
|
115 (50.2%)
|
Risk zone (awareness of KFD linked to forest usage)
|
112 (71.3%)
|
5 (6.9%)
|
117 (51.1%)
|
Transmission mode (know that KFD is transmitted by an infected tick bite)
|
57 (36.3%)
|
35 (48.6%)
|
92 (40.2%)
|
Coping (know what measures to undertake in the event of suspected KFD infection)
|
36 (22.9%)
|
10 (13.9%)
|
46 (20.1%)
|
Prevention (awareness of any prevention measures, including vaccination)
|
96 (61.1%)
|
15 (20.8%)
|
111 (48.5%)
|
Aggregated score on level of awareness
|
|
|
|
High (% with aggregate score of 4 or 5)
|
44 (28.0%)b
|
5 (6.9%)b
|
49 (21.4%)
|
Medium (% with aggregate score of 2 or 3)
|
49 (31.2%)
|
13 (18.1%)
|
62 (27.1%)
|
Low (% with aggregate score of 1)
|
20 (12.7%)
|
15 (20.8%)
|
35 (15.3%)
|
Null (% with aggregate score of 0)
|
44 (28.0%)b
|
39 (54.2%)b
|
83 (36.2%)
|
Perception about KFD
|
|
|
|
High perceived severity of KFD
|
89 (56.7%)
|
2 (2.8%)
|
91 (39.7%)
|
KFD as a major/ significant health issue in the region
|
110 (70%)
|
49 (68%)
|
159 (69%)
|
KFD not at all significant health issue in the region
|
47 (30%)
|
23 (32%)
|
70 (31%)
|
People are likely to contract KFD
|
86 (55%)
|
29 (40%)
|
115 (50%)
|
Extremely worried about contracting KFD
|
30 (19%)
|
7 (10%)
|
37 (16%)
|
Worried about contracting KFD
|
35 (22%)
|
29 (40%)
|
64 (28%)
|
Not worried about contracting KFD
|
92 (59%)
|
36 (50%)
|
128 (56%)
|
a Significant at p ≤ 0.01; b Significant at p ≤ 0.05 |
Although the overall results suggest that the majority of households had limited or no awareness about KFD (51.3%), this was particularly telling in Wayanad, with 54.2% (39/72) compared to 28% (44/157) who expressed no awareness about KFD in Shimoga, which is significantly lower (χ2 value 14.60, p < 0.05). Likewise, the proportion of households which reported high awareness of KFD was significantly higher in Shimoga (28%, 44/157) as against 6.9% (5/72) in Wayanad (χ2 value 13.04, p ≤ 0.05). A further cross-tabulation of level of awareness and risk perception (see Fig. 3) showed that as many households who expressed high awareness about KFD in Shimoga (59.1%, 26/44) also reported they were worried about contracting the disease (χ2 value 7.89, p ≤ 0.05). Similarly, the Wayanad data suggest a far lesser proportion of households who had no awareness about KFD (30.8%, 12/39) equally expressed worry about contracting it (χ2 value 14.60, p < 0.05). The disaggregated results further indicate that a greater percentage of households expressing high awareness about KFD in Shimoga (81.8%, 36/44) also perceived the disease as severe (χ2 value 16.48, p ≤ 0.01). A reverse pattern is portrayed in the Wayanad data as the percentage of households that expressed high awareness about KFD (80%, 4/5) also described the disease as not severe. This result was not statistically significant. Altogether, the above results indicate that awareness of KFD is likely to be an important driver of households’ perceived susceptibility to the disease and adaptive decision-making (see Sect. 4.5).
4.3 Dynamics of access and use of disease information services
To the extent that different disease information pathways have differing implications for local adaptive capacity, it was instructive to distinguish between access to formal and informal information7 as identified from the empirical data. This section elucidates and compares these two disease information pathways in terms of the specific channels of dissemination used by respondents and the contents of received information across the two study areas.
4.3.1 Formal disease information pathways
Figure 4 typifies the main modes by which survey respondents accessed disease information in the studied communities. As regards sources of disease information, the overall results indicate important regional differences in terms of disease information pathways. Slightly over two-thirds of households in Wayanad (70.2%) received disease advice via formal sources relative to just 22.7% of households in Shimoga falling within the same category. On the specific formal access modes, the results showed the district health department as the primary source of disease information in Shimoga (17.6%) and Wayanad (31.9%) respectively. Other important sources particularly identified in Wayanad were the Forest Department (4.3%) and the print media (10.6%). Altogether, the overall results appear to give the indication that whereas most households in Wayanad relied on formal sources for their disease advice, corresponding households in Shimoga relied on such sources to a far lesser extent (χ2 value 32.97, p < 0.05). This could have implications for design and implementation of disease information via formal sources in the Shimoga context. This could be due to geographical remoteness of some of the surveyed villages away from healthcare infrastructure and formal disease information services. Besides, the limited capacity of local health systems has meant that existing personnel are overstretched and unable to support frequent extension visits or awareness campaigns, especially outside of outbreak seasons in the affected communities. The reflections of a medical officer and taluka health officer during separate interviews in Shimoga are illustrative:
“Sir, problem is distance between houses, which is [about] 1 kilometre. See, how many houses we can visit in a day sir? We tell them to do whole village survey in a day but who is there to do, junior health assistant will be there and for 1000 population one ASHA (community health worker) will be there, in Y village population is 5 k, but only one ASHA [worker], she can’t even do at least 5 days in a day.” (DM-2, Shimoga)
“Actually, if you look at our department, we have to do preventive work and curative work also. We are under-staffed, so, for preventive itself, there should be separate staff. If I have to do OPD (outpatient care) in the morning and go to field in the noon, people will be there in the hospital, so there should be separate doctor for preventive aspects.” (TO-2, Shimoga)
To further understand the scope and content of information received (as a function of the quality of disease information), we asked the proportion of survey respondents who had prior information on KFD about two or three key messages they received as shown in Fig. 4. The overall results depict an inconsistent pattern in terms of the type and specifics of disease advice received. Whereas the majority of households in Shimoga related to information on the symptoms of KFD (67.2%), households in Wayanad (63.8%) commonly reported information relating to the modes of transmission. This notwithstanding, the overall results in Fig. 4c &d highlight two important points. First, the contrasting perspectives regarding the role of monkeys as the primary cause of KFD is quite interesting and seems to underscore the limited understanding the disease transmission pathways critical to their adaptation planning (see sub-Sect. 4.2.2). Second, the overall results surprisingly demonstrate a huge deficit in received information pertaining to coping and personal preventive measures as just 3.6% of the sub-sample (n = 166) reported receiving such information (Fig. 4d). Juxtaposing with Sect. 4.2 (Table 2), the results further reinforces the argument that households generally have limited access to credible information about KFD, particularly on coping and preventative measures. This is particularly telling as over half of the survey sample (51.3% or 118) reported limited or no awareness about KFD, despite the general acknowledgement of the disease as a significant threat to their livelihoods, health and well-being (Table 2). These results highlight a strong need to better contextualise and disseminate comprehensive risk communication messages as it is not access to information per se that affects adaptation, but the mode, scope and quality of information received.
Moreover, the qualitative interviews also revealed some underlying tensions and in a few instances, a sense of distrust between some locals and government-affiliated information brokers, with the former suspecting potential misinformation or bias in the latter’s disease risk communication. There were rumours that some forestry officials deliberately distorted aspects of risk communication by associating KFD exposure with forest usage by communities. Amid the widespread scepticism, some interviewees believed that the KFD-forest usage nexus reinforced a longstanding covert ‘agenda’ of keeping villagers out of the forest. As one forest-watcher in Shimoga, queried the so-called theory ‘tick theory’:
“I don’t know, and I don’t think tick bites will lead to this disease as we had experience with tick bites from the childhood. Even this year also. I got a good number of tick bites [he showed the interviewer his legs to ostensibly prove it] and still now am okay with my health...” (WD-5, Wayanad)
Indeed, a number of participants (belonging to the tribal groups) acknowledged their underlying ‘place-based’ vulnerabilities (as their hamlets are situated in close proximity to forests and agricultural plantations) to KFD, but expressed strong reservations about the so-called ‘tick theory’ by the Forest Department as a pretext to justify forest access restrictions. A 50-year old tribal woman and a tribal leader in Wayanad had this to say:
“We are extremely worried about KFD because we have to deal with the forest for income, and monkeys are common here, but forest officers are restricting entry into the forest and denying us access to forest products. When the monkeys are coming to our home, stealing vegetables and other things from our garden and kitchen, why are these restrictions applied?” (WD-3, Wayanad)
“Never, tick population density does not have any connection with the forest or its usage. But you should understand that there is a very clear connection between deforestation, plantation and ticks. I don’t think that we, the Kattunayakan exploit the forest and the forest products, we never had a monopoly over this…So the general attitude/ assumption that forest use causes the disease [KFD] is absolute nonsense. Every disease may have its own reason for an outbreak. But this kind of general assumption and judgment make other people feel about us as virus host.” (WD-1, Wayanad)
4.3.2 Informal disease information pathways
Given the remoteness of the surveyed communities to local healthcare infrastructure and formal disease information services, it was pertinent to investigate other (lay knowledge) sources of information were available to households. We therefore asked questions that explored other informal avenues of disease advice such as family members, friends, tribal leaders and traditional healers (as shown in Fig. 4). As discernible from Fig. 4, a significant proportion of surveyed households (76.5%) in Shimoga accessed relevant disease information mainly through family and friends as opposed to only 29.8% of corresponding households in Wayanad who did so via the same source (χ2 value 38.90, p ≤ 0.05). Juxtaposing with sub-Sect. 4.2.1, it is evident from the survey and interview data that most households in Shimoga utilised disease information received from official institutions to a much lesser extent compared with informal sources of information (including traditional/ indigenous knowledge) from within their respective villages such as other family members and friends. This survey finding is significantly supported by the interview data as almost all participants related how valuable informal information exchange between neighbouring farmers, familial groups and other local networks was central in the acquisition of relevant disease information. As a forest-watcher reflected in an interview, neighbouring households often received advice on various social and health-related concerns (including KFD-related information) from perceived local experts which they in turn disseminated to others within their social circles (WD-6, Wayanad).
The widespread recognition of the usefulness of such informal information channels in shaping local KFD knowledge was also countered by a few divergent views highlighting some potential skewness and/ or imperfections in the disease information delivery. Indeed, while conceding that local information brokers (including village chiefs, forest watchers and tribal promoters) constituted valuable sources of disease advice (given their privileged access to different kinds of information from both government and non-government sources), some interviewees implicitly referred to instances where disease information was either inadvertently misrepresented or deliberately ‘withheld’ and only shared amongst pockets of ‘closed’ network of local elites and groups, particularly those belonging to the ‘upper class’ groups. For instance, one female ASHA worker in Wayanad in emphasising the importance of a better understanding of the disease in their risk communication recounted instances where some information brokers inadvertently misrepresented KFD as primarily caused by monkeys (as the name monkey fever appear to suggest) instead of the KFDV transmission by infected ticks due to limited knowledge about the disease. As she further remarked:
“I never knew that these small ticks harm people like this. I think most people get confused with the disease name even though monkeys do not have any role in it. We should give more priority to understanding the disease. Otherwise, it always misleads [even] the ‘literate’ people. Then just imagine how ‘illiterate’ people understand this disease. Most of the news [about KFD] passed through inter-personal conversations, which again makes them [villagers] feel that monkeys are their enemies as monkeys spread the disease.” (WD-2, Wayanad)
“… Now, the monkey has been brought [by the forest officers] from outside, those monkeys will not be in the forest. Those will be around the home. That is a problem. Monkeys used to stay in the forest and was not in the habit of coming to the villages. Monkeys which are brought from the city, will not go to the forest, they will be around the houses. That is the main problem. Foresters unload the monkeys here, many people have has seen two to three vehicles [bring them in]. Everything started 15 to 20 days later after the unload…” (SA-4, Shimoga)
A number of participants further disclosed that they changed their perceptions and made new decisions after information exchange with their neighbours and friends pertaining to KFD. Within this context, the interview data further revealed that participants who had prior access to KFD-related information from formal and informal sources seem to demonstrate a clear adaptive advantage relative to those with limited or no access to disease information. The respective testaments of a tribal promoter and a medical officer in Wayanad and Shimoga during separate interviews are illustrative:
“We are aware about this disease from A to Z, even the life cycle of ticks, which seasons they are abundant, and what preventive measures are required. Even though we are not practising all of them…, we reduced number of days [traditionally spent two weeks] we live in the forest in search of honey and started wearing footwear and other natural materials to protect ourselves against tick bites…”(WD-1, Wayanad)
“We have a separate dress for work and a separate dress for home use, since previous days. I wash the dress on alternative days. We usually use tick prevention medicine for cattle once in a month or 5 months. We wash [cattle] with singe powder. We do bath daily, use oil for the body.” (SA-2, Shimoga)
These statements highlight the view that existing social networks shape the scope and quality of disease information received to a large extent. Yet, access to critical disease information via such informal brokers appeared to be somewhat differentiated along the lines of socio-cultural affiliations. A case in point is the story of a 52-year old widow belonging to a scheduled tribe in Wayanad who lamented the demise of her husband partly due to lack of prior awareness about KFD:
“When my husband passed away due to this disease that was the first time I heard of this monkey disease. Even when he was admitted in the hospital no one [in my village] told me about this disease. But when he died, people told me about the disease... He was engaged with some normal activities only, every year he went for honey collection, then medicinal plant collection and grazing…So I can’t explain how he got it [sobbing].” (WD-3, Wayanad)
4.4 Adaptive practices and utilisation of disease information
Given that disease information is critical to reducing vulnerability of households and bolstering their adaptive capacity to emerging disease risks, it was instructive to explore further how the utilisation of disease information contributed to households’ adaptive capacity in the face of the recent KFD outbreaks in the surveyed communities was further explored. In this context, respondents were first asked whether or not their respective households modified their lifestyles in response to the potential impacts of KFD (see Fig. 5, for a snapshot of the day-to-day people –environment interactions captured in a livelihood matrix). In Shimoga, whereas 42.7% of respondents affirmed that their respective households did change their lifestyles as part of their adaptation planning, 57.3% indicated otherwise. By contrast, the Wayanad data showed that none of the surveyed households altered their lifestyles in response to the potential impacts of KFD (Fig. 6). Altogether, the overall results highlight important regional differences in adaptation planning, with the majority of households (representing 60.7%) not altering their lifestyles in response to KFD and its associated impacts.
Regarding the specific coping strategies’ employed to safeguard against exposure to KFD, households that confirmed altering their lifestyles, particularly in Shimoga, were further asked about the specific ways by which they did so. As illustrated in Fig. 6a, the results show multiple coping measures employed by individual households, with vaccination uptake (52.2%), use of DMP oil (50.7%) and wearing of long clothing during visits to the forest (22.4%) as the foremost coping strategies employed. As to why nearly two-thirds of the total sample (60.7%) did not implement any adaptive measures, three common reasons were adduced by survey respondents, including the fact that KFD had not yet affected their village (56.7%), respondents were not worried about contracting KFD (19.1%) and had limited awareness about KFD (14.8%). Further disaggregation by study area revealed marked regional differences in responses relating to the absence of KFD in some villages, as at the time of the survey, as the primary reason for inaction. For instance, the Wayanad data indicates that households that cited the absence of KFD in their villages as the key reason for their inaction constituted more than double (63.9%) the proportion of surveyed households in Shimoga (29.3%) reporting same (χ2 value 24.57, p ≤ 0.01). The survey results are corroborated by the interviews as most participants expressed the lack of prior knowledge and/ or awareness of the disease emergence in their village as the underlying reason for the limited implementation of adaptive measures.
To address the question of how the utilisation of disease information contributed to households’ adaptive capacity, a further cross-tabulation analysis was undertaken. When disaggregated by study area, the Shimoga data showed no significant association between access to disease information and alteration of lifestyles, as the majority of households who had awareness of KFD did not modify their lifestyles as the result of the disease emergence. At face-value, these results seem to rather puzzlingly contradict the a priori assumption that access to disease information is an essential prerequisite for adaptation planning. Yet, further cross-tabulation analysis revealed that as many households that had prior experience of KFD in Shimoga (68.4%, 26/38) also reported altering their lifestyles following the disease emergence (χ2 value 10.72, p ≤ 0.05). This gives the indication that prior experience rather than awareness of disease risk per se influences adaptive behaviour. As our interview data confirms, the overall picture of adaptive decision-making is more nuanced and complex. Indeed, most participants expressed limited belief in their own ability (agency) to change their circumstance, which invariably constrained the translation of received disease information into substantive adaptive action. For instance, a number of interviewees in response to the question of how they adapted to KFD worriedly remarked “we believe in God to protect us”, suggesting that they were resigned to their fate in the face of a looming disease risk. While this finding may in some sense cursorily connote limited opportunities for utilising disease information to inform substantive adaptive actions, critically however, it implicitly echoes the view that individuals and households’ understanding and realities of KFD are socially and culturally constructed. To the extent that this inference holds true, then it also conveys the understanding that the lived realities and perceptions of local communities about (zoonotic) disease risks cannot be divorced from underlying socio-cultural beliefs and practices [33, 34]. Moreover, the limited agency of households could be indicative of other pre-existing structural inequalities which operated to constrain their capacity to act on received disease advice in practice. In fact, a recurrent theme from the interviews was that aside from the seasonal impacts of KFD, other socio-economic inequalities and issues not only limited their ability to cope but significantly exacerbated the impact of the disease stress. Two typical views in this regard were given by a PHC medical officer stationed in Shimoga and tribal leader in Wayanad:
“See to be honest, the number of deaths that occurred here did not happen anywhere else. Why were there more deaths? If we were to contemplate on this, especially in this village, it would be due to many factors. Low socio-economic status, poor nutrition, and poor immunity…Talking about the minimum lethal dose of virus, due to the high tick positivity density, tick bites are higher, and the viral load is higher. That’s why the deaths are higher.” (DM-2, Shimoga)
“Elderly people [are] more vulnerable as the intake of alcohol is good quantity and malnourished women comes second as most of them are not eat proper food properly. Even we are getting subsidised food grain for free but we are unable to improve their condition…If you see the average age of death case, you can actually understand my points.”(WD-1, Wayanad)
These observations reinforce Bardosh et al.’s [13] argument that different group of people respond differently to disease interventions owing to differences in their socio-economic capacities.
4.5 Disease adaptation in practice – looking beyond the ‘techno-managerial’ approach to KFD vaccination
The lack of specific treatment vis-à-vis the seasonality of KFD outbreaks (November to May) has meant that vaccination remains the single-most important adaptive strategy to the disease [22, 28, 29]. Yet, in Table 2, the overall results suggest a limited uptake of vaccination (46.7%), despite nearly two-thirds of the sample (72.5% or 166) having had prior information about KFD (χ2 value 4.865, p ≤ 0.05). Although consistent with the literature and thus not surprising, it is particularly telling that of the proportion of households who had prior information about KFD in Wayanad (65.3%), only 19.4% were reportedly vaccinated against KFD (χ2 value 9.244, p ≤ 0.05). Further cross-tabulation analysis revealed statistically significant differences between socio-economic characteristics and vaccination, with uptake strongly influenced by caste affiliation, poverty, prior experience of KFD, and awareness of KFD transmission pathways. For instance, the disaggregated results indicate that lower-caste households reported higher vaccination uptake than upper-caste households (χ2 value 15.569, p ≤ 0.05). Likewise, a higher percentage of BPL households relative to APL households reported uptake of vaccination against KFD (χ2 value 15.100, p ≤ 0.05). Further disaggregation by awareness of KFD transmission by infected tick-bites and repeating the above quantitative comparisons, we found that a far lesser proportion of households who did not perceive KFD as severe claimed to be vaccinated as against household indicating otherwise. Moreover, the overall results also indicate significant differences between prior experience of KFD and vaccination status. For instance, a higher percentage of households that reported prior experience of KFD in Shimoga (78.9%, 30/38) also claimed being vaccinated against it (χ2 value 6.34, p ≤ 0.05). A similar picture is depicted in the Wayanad data with the majority of households with no prior experience of KFD reported not being vaccinated against it (χ2 value 6.13, p ≤ 0.05).
These results (which are also supported by our interview data) seems to put to question the simplistic stereotypical view that marginalised populations are less receptive to vaccination against KFD. Nuancing this narrative, they convey the understanding that the supposed hesitance or reticence of vulnerable groups to KFD vaccination could well be attributable to the limited access to quality disease information and to some extent, the often-overlooked but deep-seated [trust] concerns about the efficacy current vaccine. The fact that a higher percentage of households that expressed awareness of KFD transmission by infected tick-bites (45.8%) as against households stating otherwise (1.9%) equally reported vaccination uptake, further buttresses this observation (χ2 value 15.100, p ≤ 0.01). Indeed, participants during the interviews flagged a myriad of concerns about the existing vaccine (including lack of knowledge, required multiple-doses, inappropriate timing, and pain) which hampered widespread uptake of vaccination, especially in Wayanad. Reflecting the need for improvement in the existing vaccine, a male KFD survivor (plantation worker) in Shimoga said:
“This time nothing is done, why you know there was a positive case this time but they had taken booster dose. This means vaccination, not effective I feel. It is useless…Health department people advice, they really tried well but we don’t know why it [KFD] comes?” (SA-3, Shimoga)
These sentiments were also widely shared by the disease managers as well:
“Only problem is with, in my view, the vaccine…vaccine is the main hitches. Because the acceptance of that vaccine is not so [great]… welcoming sign is not seen. One more point is the doses also. We need to give multiple doses to get what we need. To get some protection he/she needs to take full course. After that every year he/she needs to get booster dose for five years. Those are all hitches. I think one single injection that can protect the person for five years is needed....” (DO-3, Shimoga)
“…We are struggling with the age-old vaccine, which was prepared in the 90 s I think. We are going with the same. We don’t know about the strain change…the virus... Even the research has not [been] done. Even the cases which (who were) vaccinated fully, also were [re]infected. So, for that we need to do some research on whether the prevalence has changed it or not.”(DO-4, Shimoga)
Another important barrier to households’ uptake of vaccination relates to the existing religio-cultural beliefs and practices. It was gathered from the interviews that some participants particularly those of scheduled tribe or caste backgrounds strongly perceived vaccination as something ‘alien’ from their long-standing religio-cultural belief systems. A tribal leader from Wayanad was quite critical of about the ‘techno-administrative’ approach to KFD vaccination highlighting that “I am totally against the vaccination strategy of the government, until I get clear knowledge how the vaccination works in our body to prevent the KFD and both advantage and disadvantage of taking vaccine…” (WD-4, Wayanad). Corroborating this stance was another tribal promoter from Kattunayakan village (in Wayanad), reflecting on his own experiences with KFD vaccination, posited that despite the government’s free supply of protein-contented food (including milk, boiled eggs etc.) as way of incentivising vaccine uptake, some tribal groups were still somewhat reticent suggesting “it was not in our blood, mostly people who are above 40 never taken any vaccine”. The tribal promoter further remarked:
“We [Kattunayakan] are not that much literate and we speak another dialect, and most of the young people can follow the Malayalam language very easily but the people above 45 will not understand what people speaks about. So it was me who convinced the people and myself I was struggling to understand how serious it [KFD] was. And it took almost a year to understand the risk of KFD, meanwhile we lost more than 16 people.” (WD-1, Wayanad)
Other important contextual factors that impeded widespread vaccination uptake that emerged from the interviews were the limited health extension and inaccessibility of some villages. Altogether this conveys the understanding that maintenance of social relations and networks were important avenues for receiving disease information, which in turn shaped the ability to adapt. This is consistent with the observation that lived experiences and perceptions cannot be divorced from their socio-cultural beliefs. It therefore follows that trust building and concerted community sensitization remain important to obtain the requisite buy-in and demystify otherwise deep-seated (anti)vaccination perceptions.
Aside from vaccination, livelihood diversification emerged as another important coping strategy adopted by households following the KFD outbreak. A number of participants narrated how they have had to temporally switch from the collection of non-timber forest products (NTFPs) such as honey and firewood to wage labour. Even so, such adaptive action was contingent on the availability of such non-forest based jobs and some had to care for ailing relatives, implying they had limited time to effectively engage in alternative work. Whereas government intervention through (alternative) employment and social welfare schemes have in some respects afforded a potential leeway to adapt, thus alleviating the otherwise grave impacts of the outbreak, it was also gathered that the implementation of these support schemes had inadvertently contributed to other unanticipated maladaptation consequences. According to another Kattunayakan tribal leader, whereas some households managed to secure temporary employment as construction labourers (earning on average Rs. 900 [£9.60] per day), this coping strategy nonetheless occasioned and/or exacerbated other existing communal problems, including ‘adulteration’ of traditional value systems, ‘politicisation’ of tribal women, and alcoholism amongst others:
“The one which I felt very personally, that is government intervention through the employment schemes and its implementation is taking this community away from how they lived so far. I am not blaming the government, neither the employment scheme, but unfortunately as we are tribe, we should have something unique (that we going to lose). Our name then (kurmar) is going to be lost. As the disease spreads, the government brings more restrictions and forest use will become impossible. You can call it an identity crisis of the tribe, but I am sure, the coming generation will never follow the rituals as we practice now…” (WD-1, Wayanad)
6The ‘Below Poverty Line’ is a benchmark used by the Indian government to highlight socio-economic disadvantage and to identify individuals and households in need of government assistance. The BPL is estimated using several parameters which varies from state to state and within states. However, as a general rule of thumb, the poverty line is Rs. 32 (£ 0.35) for rural areas and Rs. 47 (£ 0.51) for urban areas of India [see 55].
7Formal information refers to the set of information and messages relevant for the prevention and control of KFD generated and/ or disseminated via official institutions or pathways. Conversely, informal information refers to the all the related information and messages received through unofficial channels, including community leaders.