| Literature DB >> 35766676 |
Wuelton Monteiro, Stephan Karl, Andrea Kuehn, Anne Almeida, Michael White, Sheila Vitor-Silva, Gisely Melo, Jose Diego Brito-Sousa, Djane Clarys Baia-da-Silva, Alexandre Vilhena Silva-Neto, Vanderson Sampaio, Quique Bassat, Ingrid Felger, Ivo Mueller, Marcus Lacerda.
Abstract
BACKGROUND: Understanding the epidemiology of malaria through the molecular force of the blood-stage infection of Plasmodium vivax (molFOB) may provide a detailed assessment of malaria transmission.Entities:
Mesh:
Year: 2022 PMID: 35766676 PMCID: PMC9239689 DOI: 10.1590/0074-02760210330
Source DB: PubMed Journal: Mem Inst Oswaldo Cruz ISSN: 0074-0276 Impact factor: 2.747
Fig. 1:spatial representation of clinical Plasmodium vivax and Plasmodium falciparum cases. (A) South America; (B) Amazonas state; (C) Manaus municipality and study; (D) quantitative polymerase chain reaction (qPCR) detected P. vivax; (E) P. falciparum infections. Data are shown as incidence (cases/detections per person per year, aggregated to the household level). Increased diameter of the circles represents increased incidence. Maps were created using QGIS 2.18, with geodata collected for this study.
Baseline characteristics of the population enrolled in the study
| Variable | Nº of participants N = 1,274 | % |
| Gender | ||
| Male | 651 | 51.1 |
| Age group (years) | ||
| < 10 | 368 | 28.9 |
| 10-20 | 634 | 49.6 |
| 21-60 | 128 | 10.0 |
| ≥ 61 | 160 | 12.5 |
| Occupation | ||
| Agriculture | 179 | 14.1 |
| Office worker | 170 | 13.3 |
| House wife | 218 | 17.1 |
| Pre-school children | 175 | 13.7 |
| School children | 331 | 26.0 |
| Retired | 63 | 5.0 |
| Unemployed/Other | 138 | 10.8 |
| Previous infection (number) in the last two months | ||
| 1-3 | 364 | 28.6 |
| > 3 | 504 | 39.6 |
| Infection in past two weeks | 17 | 1.3 |
| Antimalarial in past two months | 40 | 3.2 |
| More than two months of residency | 1,201 | 94.9 |
| Community | ||
| Ipiranga | 430 | 33.8 |
| Brasileirinho | 416 | 32.7 |
| Puraquequara | 428 | 33.6 |
Fig. 2:infection prevalence, molecular force of Plasmodium vivax infection and rainfall within the three communities. (A) prevalence of P. vivax infection in the three communities, and in in the entire study population; (B) prevalence of Plasmodium falciparum infection in the three communities, and in in the entire study population; (C) molecular force of P. vivax blood stage infection (molFOB) in the three communities and in the entire population; (D) rainfall and incidence of P. vivax and P. falciparum infections detected by polymerase chain reaction (PCR) in the entire study area.
Risk factors associated with Plasmodium vivax positivity, P. vivax clinical disease, and Plasmodium falciparum positivity. Adjusted hazards ratio (aHR) was calculated using a multiple failure time model
| Risk factor |
|
|
| |||
| aHR | p | aHR | p | aHR | p | |
| Community (ref. Ipiranga) | ||||||
| Season (Ref: Jun-Nov) | 2.56 (1.89-5.74) | < 0.001 | 10.56 (2.36-47.19) | 0.002 | 0.08 (0.01-0.51) | 0.008 |
| Brasileirinho | 1.01 (0.4-1.08) | 0.002 | 0.11 (0.05-0.23) | < 0.001 | 0.04 (0.01-0.26) | < 0.001 |
| Puraquequara | 2.39 (1.11-2.31) | 0.26 (0.14-0.5) | 0.23 (0.07-0.71) | |||
| Age group (ref. 1-10) | ||||||
| 10-20 | 1.36 (0.78-1.95) | 0.001 | 1.01 (0.54-1.88) | 0.02 | 0.78 (0.19-3.27) | 0.300 |
| 21-60 | 2.22 (1.1-2.45) | 0.63 (0.36-1.13) | 1.33 (0.39-4.5) | |||
| ≥ 61 | 1.9 (0.71-2.15) | 0.15 (0.04-0.63) | 2.15 (0.47-9.94) | |||
| Employed in agriculture
| 0.82 (0.52-1.12) | 0.162 | 0.43 (0.25-0.74) | 0.002 | 1.48 (0.41-5.29) | 0.546 |
| Male | 1.21 (0.91-1.62) | 0.187 | 1.16 (0.77-1.75) | 0.482 | 1 (0.4-2.47) | 0.996 |
| Bednet usage
| 1.06 (1.01-1.08) | 0.005 | 1.06 (1.01-1.11) | 0.018 | 0.95 (0.85-1.06) | 0.322 |
| Travel frequency2 | 0.99 (0.99-1.01) | 0.516 | 1.01 (1-1.01) | 0.02 | 1 (0.95-1.05) | 0.934 |
| House treated with IRS2 | 0.96 (0.92-0.99) | 0.022 | 0.92 (0.86-0.98) | 0.008 | 1.08 (0.94-1.23) | 0.278 |
| Windows protected by screen
| 0.78 (0.72-1.37) | 0.958 | 1.56 (0.87-2.8) | 0.135 | 1.05 (0.27-4.08) | 0.946 |
| Reported previous malaria | 1.11 (0.56-1.58) | 0.814 | 0.66 (0.17-2.64) | 0.558 | 9.65 (4.45-20.92) | < 0.001 |
a: status at enrolment; b: as time-changing covariate (average observed at time of outcome); c: average bednet usage was defined as the proportion of times a person had answered `yes’ to the question: `Did you sleep under a bednet last night’ during ACD; IRS: indoor residual spraying.
Fig. 3:distribution of Plasmodium infections in the study population. (A) heterogeneity in the incidence of malaria infections; (B) P. vivax molFOB over the entire year of follow-up.
Factors associated with Plasmodium vivax molecular force of infection (molFOB). Adjusted incidence rate ratio (aIRR) was calculated using a negative binomial regression model
| Risk factor |
| |
| aHR | p | |
| Community (ref. Ipiranga) | ||
| Brasileirinho | 0.47 (0.31-0.71) | < 0.001 |
| Puraquequara | 0.98 (0.69-1.39) | |
| Age group (ref. 1-10) | ||
| 10-20 | 1.15 (0.73-1.82) | |
| 21-60 | 1.06 (0.71-1.60) | 0.420 |
| ≥ 61 | 0.75 (0.43-1.29) | |
| Employed in agriculture
| 1.22 (0.81-1.83) | 0.350 |
| Male | 1.20 (0.91-1.58) | 0.200 |
| Bed net usage
| 1.63 (1.24-2.15) | < 0.001 |
| Travel frequency
| 1.00 (0.92-1.10) | 0.950 |
| House treated with IRS2 | 0.88 (0.66-1.16) | 0.360 |
| Windows protected by screen1 | 1.04 (0.74-1.45) | 0.840 |
| Reported previous malaria | 3.02 (2.02-4.53) | < 0.001 |
a: status at enrolment; b: as time-changing covariate (average observed at time of outcome); c: average bed net usage was defined as the proportion of times a person had answered `yes’ to the question: `Did you sleep under a bed net last night’ during ACD; IRS: indoor residual spraying.