| Literature DB >> 25966028 |
Amélé N Wotodjo1, Jean-François Trape2, Vincent Richard3, Souleymane Doucouré4, Nafissatou Diagne4, Adama Tall3, Ousmane Ndiath5, Ngor Faye6, Jean Gaudart7, Christophe Rogier8, Cheikh Sokhna4.
Abstract
BACKGROUND: The human landing catches is the gold standard method used to study the vectors of malaria and to estimate their aggressiveness. However, this method has raised safety concerns due to a possible increased risk of malaria or other mosquito-borne diseases among the mosquito collectors. The aim of this study was to evaluate the incidence of malaria attacks among mosquito collectors and to compare these results with those of non-collectors in a Senegalese village.Entities:
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Year: 2015 PMID: 25966028 PMCID: PMC4428811 DOI: 10.1371/journal.pone.0126187
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Socio-demographic and others characteristics among mosquito collectors and non-collectors in Dielmo (n = 3,812) using a random-effect logistic regression.
| Characteristics | Non-collectors (%) | Collectors (%) | OR (95% CI) |
|
|---|---|---|---|---|
|
| 2,440 | 1,372 | ||
|
| ||||
| No | 2,286 (93.7) | 1,286 (93.7) | 1 | |
| Yes (at least one) | 154 (6.3) | 86 (6.3) | 1.09 (0.75–1.58) | 0.66 |
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| ||||
| 0 | 2,286(93.7) | 1,286 (93.7) | 1 | |
| 1 | 134 (5.5) | 84 (6.1) | 1.16 (0.79–1.70) | 0.45 |
| 2 and more | 20 (0.8) | 2 (0.2) | 0.29 (0.04–1.90) | 0.20 |
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| Without | 1,959 (80) | 1,086 (79) | 1 | |
| With | 481 (20) | 286 (21) | 1.004 (0.81–1.25) | 0.97 |
|
| ||||
| 0 | 1,959 (80) | 1,027 (75) | 1 | |
| 1 | 401 (16) | 268 (20) | 1.25 (0.99–1.56) | 0.06 |
| 2 | 62 (3) | 61 (4) | 2.1 (1.32–3.35) | <0.01 |
| 3 or more | 18 (1) | 16 (1) | 1.65 (0.71–3.81) | 0.24 |
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| ||||
| 15–29 years old | 953 (30) | 662 (48) | 1 | |
| 30–44 years old | 630 (26) | 372 (27) | 0.38 (0.27–0.52) | <0.01 |
| 45 years old and over | 857 (35) | 338 (25) | 0.14 (0.09–0.21) | <0.01 |
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| ||||
| No | 566 (23) | 171 (13) | 1 | |
| Yes | 1,815 (74) | 1,201 (88) | 3.94 (1.89–8.23) | <0.01 |
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| ||||
|
| ||||
| AA | 2,136 (88) | 1,194 (87) | 1 | |
| AS | 240 (10) | 161 (12) | 0.93 (0.33–2.68) | 0.90 |
| AC | 39 (2) | 15 (1) | 0.77 (0.04–15.68) | 0.87 |
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| ||||
| O | 817 (33) | 456 (33) | 1 | |
| A | 835 (34) | 481 (35) | 0.98 (0.43–2.23) | 0.95 |
| B | 644 (26) | 384 (28) | 1.53 (0.65–3.61) | 0.33 |
| AB | 93 (4) | 38 (3) | 1.39 (0.28–6.97) | 0.69 |
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| Quinimax | 736 (30) | 368 (27) | 1 | |
| Chloroquine | 543 (22) | 463 (34) | 2.84 (2.17–3.73) | <0.01 |
| AQ+SP/ACT | 522 (21) | 198 (14) | 0.41 (0.30–0.55) | <0.01 |
| ACT+LLINs | 639 (26) | 343 (25) | 0.66 (0.49–0.87) | <0.01 |
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| First quarter of the year | 566 (23) | 275 (20) | 1 | |
| Second quarter of the year | 619 (25) | 329 (24) | 1.2 (0.94–1.54) | 0.15 |
| Third quarter of the year | 652 (27) | 388 (28) | 1.34 (1.04–1.71) | 0.02 |
| Fourth quarter of the year | 603 (25) | 380 (28) | 1.39 (1.08–1.77) | 0.01 |
OR: Odds ratio.
Fig 1Malaria incidence among mosquito collectors and non-mosquito collectors according to different periods in Dielmo.
Fig 2Malaria incidence among mosquito collectors and non-mosquito collectors according to age group in Dielmo.
Socio-demographic and biological characteristics according to malaria attacks and results of random-effect negative binomial regression models exploring factors associated with clinical malaria cases (n = 3,812).
| Characteristics | Subcategory | Number of persons n = 199 (100%) | Number of person-trimester n = 3,812 (100%) | Clinical malaria cases | Simple regression analysis | Multiple regression analysis | |||
|---|---|---|---|---|---|---|---|---|---|
| No n = 3,572 n (%) | Yes n = 240 n (%) | IRR (95% CI) |
| aIRR (95% CI) |
| ||||
|
| No | - | 2,440 (64) | 2,286 (64) | 154 (64) | 1 | 1 | ||
| yes | - | 1,372 (36) | 1,286 (36) | 86 (36) | 0.97 (0.71–1.33) | 0.85 | 0.89 (0.65–1.22) | 0.47 | |
|
| 0 | - | 2,440 (64) | 2,286 (64) | 154 (64) | 1 | |||
| 1 | - | 461 (12) | 430 (12) | 31 (13) | 0.94 (0.62–1.42) | 0.77 | |||
| 2 | - | 445 (12) | 418 (12) | 27 (11) | 0.94 (0.60–1.48) | 0.80 | |||
| 3 and more | - | 466 (12) | 438 (12) | 28 (12) | 1.05 (0.67–1.66) | 0.83 | |||
|
| 15–29 years old | - | 1,615 (42) | 1,478 (41) | 137 (57) | 1 | 1 | ||
| 30–44 years old | - | 1,002 (26) | 937 (27) | 65 (27) | 0.59 (0.41–0.87) | <0.01 | 0.59 (0.40–0.88) | <0.01 | |
| 45 years old and over | - | 1,195 (31) | 1,157 (32) | 38 (16) | 0.27 (0.16–0.45) | <0.01 | 0.31 (0.18–0.53) | <0.01 | |
|
| No | 65 (33) | 796 (21) | 714 (20) | 82 (34) | 1 | 1 | ||
| Yes | 134 (67) | 3,016 (79) | 2,858 (80) | 158 (66) | 0.32 (0.19–0.54) | <0.01 | 0.38 (0.24–0.61) | <0.01 | |
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|
| AA | 167 (84) | 3,330 (87) | 3,120 (87) | 210 (88) | 1 | |||
| AS | 22 (11) | 401 (11) | 381 (11) | 20 (8) | 0.82 (0.39–1.76) | 0.62 | |||
| AC | 2 (1) | 54 (1) | 51 (1) | 3 (1) | 0.50 (0.06–4.15) | 0.52 | |||
|
| O | 63 (32) | 1,273 (33) | 1,187 (33) | 86 (36) | 1 | |||
| A | 57 (29) | 1,316 (35) | 1,224 (34) | 92 (38) | 1.08 (0.61–1.91) | 0.80 | |||
| B | 48 (24) | 1,028 (27) | 978 (27) | 50 (21) | 0.70 (0.37–1.32) | 0.27 | |||
| AB | 9 (5) | 131 (3) | 126 (4) | 5 (2) | 0.59 (0.15–2.29) | 0.45 | |||
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| Quinimax | 104 | 1,104 (29) | 1,031 (29) | 73 (30) | 1 | 1 | ||
| Chloroquine | 106 | 1,006 (26) | 913 (26) | 93 (39) | 1.07 (0.76–1.49) | 0.70 | 1.16 (0.77–1.75) | 0.49 | |
| AQ+SP/ACT | 110 | 720 (19) | 678 (19) | 42 (18) | 0.58 (0.38–0.88) | 0.01 | 0.74 (0.48–1.16) | 0.19 | |
| ACT+LLINs | 119 | 982 (26) | 950 (27) | 32 (13) | 0.28 (0.18–0.45) | <0.01 | 0.43 (0.27–0.70) | <0.01 | |
|
| First quarter of the year | 166 | 841 (22) | 801 (22) | 40 (17) | 1 | 1 | ||
| Second quarter of the year | 169 | 948 (25) | 899 (25) | 49 (20) | 0.98 (0.66–1.46) | 0.92 | 0.96 (0.65–1.42) | 0.84 | |
| Third quarter of the year | 182 | 1,040 (27) | 963 (27) | 77 (32) | 1.41 (0.97–2.04) | 0.07 | 1.31 (0.88–1.95) | 0.19 | |
| Fourth quarter of the year | 173 | 983 (25) | 909 (25) | 74 (31) | 1.53 (1.06–2.20) | 0.02 | 1.47 (1.02–2.13) | 0.04 | |
|
| - | 1.007 (1.004–1.01) | <0.01 | 1.003 (0.999–1.007) | 0.10 | ||||
IRR: Incidence rate ratio; aIRR: adjusted incidence rate ratio.
Random-effect logistic regression models exploring factors associated with asymptomatic malaria infection (n = 3,812).
| Characteristics | Subcategory | Simple regression analysis | Multiple regression analysis | ||
|---|---|---|---|---|---|
| OR (95% CI) |
| aOR (95% CI) |
| ||
|
| |||||
|
| No | 1 | 1 | ||
| yes | 1.03 (0.85–1.26) | 0.73 | 0.88 (0.71–1.09) | 0.23 | |
|
| 0 | 1 | |||
| 1 | 0.90 (0.68–1.19) | 0.47 | |||
| 2 | 1.08 (0.82–1.43) | 0.59 | |||
| 3 and more | 1.16 (0.88–1.53) | 0.29 | |||
|
| 15–29 years old | 1 | 1 | ||
| 30–44 years old | 0.33 (0.25–0.43) | <0.01 | 0.40 (0.30–0.52) | <0.01 | |
| 45 years old and over | 0.21 (0.15–0.30) | <0.01 | 0.38 (0.28–0.52) | <0.01 | |
|
| No | 1 | |||
| Yes | 1.17 (0.83–1.65) | 0.37 | |||
|
| |||||
|
| AA | 1 | 1 | ||
| AS | 1.04 (0.66–1.64) | 0.85 | 0.73 (0.48–1.11) | 0.15 | |
| AC | 2.45 (0.75–8.03) | 0.14 | 3.15 (1.08–9.19) | 0.04 | |
|
| O | 1 | |||
| A | 0.81 (0.57–1.17) | 0.26 | |||
| B | 1.02 (0.70–1.49) | 0.92 | |||
| AB | 0.69 (0.31–1.51) | 0.35 | |||
|
| Quinimax | 1 | 1 | ||
| Chloroquine | 0.61 (0.49–0.76) | <0.01 | 0.65 (0.49–0.84) | <0.01 | |
| AQ+SP/ACT | 0.20 (0.14–0.27) | <0.01 | 0.26 (0.19–0.35) | <0.01 | |
| ACT+LLINs | 0.03 (0.02–0.05) | <0.01 | 0.05 (0.03–0.07) | <0.01 | |
|
| First quarter of the year | 1 | 1 | ||
| Second quarter of the year | 1.26 (0.98–1.62) | 0.07 | 1.29 (0.99–1.68) | 0.06 | |
| Third quarter of the year | 1.57 (1.23–2.00) | <0.01 | 1.48 (1.11–1.97) | <0.01 | |
| Fourth quarter of the year | 1.32 (1.03–1.69) | 0.03 | 1.29 (0.99–1.69) | 0.06 | |
|
| 1.008 (1.006–1.009) | <0.01 | 1.003 (1.00–1.01) | 0.023 | |
OR: Odds ratio; aOR: adjusted odds ratio.