| Literature DB >> 35847777 |
Rahim Ali Ahmed1,2, Hari Shankar3, Syed Shah Areeb Hussain2, Ananta Swargiary4, Avdhesh Kumar5, Mohammad Tarique6, Pankaj Prabhakar7, Harpal Singh Suri1, Kuldeep Singh8, Joy Kumar Chakma3, Jyoti Singh9, Afluza Begum10.
Abstract
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 (rs = 0.69, 90%CI; p = 0.06) and slide positivity rate (rs = 0.83, 95%CI; p = 0.01). Older people were less educated (rs = -0.66; p < 0.001), had lesser knowledge about malaria cause (rs = -0.42; χ2=21.80; p < 0.001) and prevention (rs = -0.18; p = 0.04). Malaria control practices were followed by those having knowledge about cause of malaria (rs = 0.36; χ2 = 13.50; p < 0.001) and prevention (rs = 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.Entities:
Keywords: Anopheles; climate; community participation; malaria; outbreak
Year: 2022 PMID: 35847777 PMCID: PMC9280886 DOI: 10.3389/fmed.2022.913848
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
Figure 1Map of study area (Red color depicts the area covered under the Dolonibasti sub-center).
Figure 2Malaria epidemiological trend from 2011 to 2018. (A) Entire Udalguri district, (B) Khoirabari BPHC, (C) Orang BPHC, and (D) Udalguri BPHC.
Malaria epidemiology in the Dolonibasti sub-center.
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| 2011 | 6,837 | 5865 | 1,100 | 1047 | 53 | 85.78 | 160.89 | 18.76 | 17.85 | 95.18 | 4.82 | 0 |
| 2012 | 6,878 | 4179 | 753 | 695 | 58 | 60.76 | 109.48 | 18.02 | 16.63 | 92.30 | 7.70 | 0 |
| 2013 | 7,013 | 3309 | 407 | 399 | 8 | 47.18 | 58.04 | 12.30 | 12.06 | 98.03 | 1.97 | 0 |
| 2014 | 7,224 | 7218 | 1,067 | 896 | 171 | 99.92 | 147.70 | 14.78 | 12.41 | 83.97 | 16.03 | 0 |
| 2015 | 7,994 | 5911 | 1,326 | 953 | 373 | 73.94 | 165.87 | 22.43 | 16.12 | 71.87 | 28.13 | 0 |
| 2016 | 8,073 | 5635 | 1,389 | 955 | 434 | 69.80 | 172.05 | 24.65 | 16.95 | 68.75 | 31.25 | 0 |
| 2017 | 8,150 | 4044 | 934 | 746 | 188 | 49.62 | 114.60 | 23.10 | 18.45 | 79.87 | 20.13 | 0 |
| 2018 | 8,188 | 6633 | 2,136 | 1734 | 402 | 81.01 | 260.87 | 32.20 | 26.14 | 81.18 | 18.82 | 0 |
| 2019 | 8,271 | 6218 | 314 | 230 | 84 | 75.18 | 37.96 | 5.05 | 3.70 | 73.25 | 26.75 | 0 |
| 2020 | 8,345 | 5146 | 73 | 43 | 30 | 61.67 | 8.75 | 1.42 | 0.84 | 58.90 | 41.10 | 0 |
| 2021 | 8,496 | 5023 | 8 | 3 | 5 | 59.12 | 0.94 | 0.16 | 0.06 | 37.50 | 62.50 | 0 |
Pf, Plasmodium falciparum; Pv, Plasmodium vivax; ABER, Annual Blood Examination Rate; API, Annual Parasitic Incidence; SPR, Slide Positivity Rate; SFR, Slide Falciparum Rate.
Figure 3Number of malaria cases reported in the Dolonibasti sub-center and its adjoining two sub-centers of Orang BPHC. (A) Month wise incidence of malaria cases during 2013–18. (B) Weekly incidence of malaria cases during 2018 and (C) Month wise incidence of malaria cases during 2018 in the Dolonibasti sub-center and it's adjoining two sub-centers namely Nagao Panbari and Kadabil.
Larval density of mosquito species in the Dolonibasti sub-center.
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| Drain in residential colony | 11 ± 3.5 |
| Medium |
| Agricultural canal | 9 ± 3.5 |
| Medium |
| Tea estate canal | 10 ± 3.5 |
| Medium |
| Paddy field | 16 ± 3.5 |
| Medium |
| Other containers | 5 ± 3.5 |
| Medium |
Density–Low, 1–4, Medium, 5–60 and High = >60.
Figure 4Scatter plots of Malaria Cases and (A) Temperature, (B) Relative Humidity, and (C) Rainfall. (D) Represents the results of Spearman's Correlation of malaria cases with monthly climatic parameters (2013–2018). Color of the correlation plot (D) indicates the magnitude of the association, whereas size of the box indicates statistical significance, with big boxes indicating high significance values.
Knowledge, Attitude and Practices related to malaria among respondents (n = 120) in the Dolonibasti sub-center, 2018.
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| 9–14 year | 9 | 7.50 |
| 15–25 year | 38 | 31.67 |
| 26–50 year | 56 | 46.67 |
| 51 years and above | 17 | 14.17 |
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| Illiterate | 74 | 61.67 |
| Up to Primary | 16 | 13.33 |
| Up to Upper Primary | 19 | 15.83 |
| Up to High School | 11 | 9.17 |
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| No symptom | 29 | 24.17 |
| Fever only | 46 | 38.33 |
| Fever with chill | 13 | 10.83 |
| Headache | 18 | 15.00 |
| Body ache | 7 | 5.83 |
| Vomiting | 6 | 5.00 |
| Others | 1 | 0.83 |
| Don't know | 0 | 0.00 |
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| Government Agency | 95 | 79.17 |
| Private Agency | 11 | 9.17 |
| Others (Pharmacy/Quack) | 14 | 11.67 |
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| Yes | 2 | 1.67 |
| No | 118 | 98.33 |
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| Yes | 53 | 44.17 |
| No | 67 | 55.83 |
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| Yes | 81 | 67.50 |
| No | 39 | 32.50 |
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| Correct | 94 | 78.33 |
| Wrong | 26 | 21.67 |
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| Correct | 87 | 72.50 |
| Wrong | 33 | 27.50 |
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| Yes | 68 | 56.67 |
| No | 52 | 43.33 |
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| Economic conditions | 8 | 15.77 |
| Do not know/answer | 12 | 23.08 |
| Ignorance | 23 | 44.23 |
| Do not care | 9 | 17.31 |
Figure 5Spearman's rank Correlation test between the KAP parameters. Crosses indicate no relationship between the variables (i.e., non-significant association p-value > 0.1). The color of circles in the plot indicates the magnitude of the association (as per the scale bar), whereas the size of the circle indicates the significance (larger size indicates higher significance i.e., lower p-value).
Figure 6Mosaic Plots of significantly associated KAP variables. Width of the boxes indicates the proportion of respondents, whereas the height of the boxes indicates the proportion of each row variable. Colors indicate the range of the standard residuals estimated by calculating the difference between the observed values and expected values due to random chance.