Literature DB >> 33085704

Factors associated with malaria in indigenous populations: A retrospective study from 2007 to 2016.

Bruna Martins Meireles1, Vanderson de Souza Sampaio2,3,4, Wuelton Marcelo Monteiro2,3, Maria Jacirema Ferreira Gonçalves1,5.   

Abstract

BACKGROUND: In Brazil malaria is most frequent in the Amazon region, mainly in the Amazonas state, where it is found the most proportion of indigenous people of the whole country. It is remarkable publications about malaria in the Amazon, although information on malaria in indigenous populations is still poorly explored.
OBJECTIVE: Identify factors associated with malaria in indigenous populations.
METHODS: Cross-sectional study of positive cases of malaria in the state of Amazonas, Brazil, from 2007 to 2016. Secondary data were obtained from the Epidemiological Surveillance Information System for Malaria and from the Mortality Information System, both from Brazil. To tackle with race missing data, cases with no race fulfilled were classified according to the probable location where infection occurred. This way, was imputed indigenous race for those which the probable infection location was indigenous village (aldeia). Variables tested with race were: sex, age, schooling, microscope surveillance slide type, parasitic infection species, parasitemia level, and timeliness of treatment. Multivariate logistic regression was used.
RESULTS: A total of 1,055,852 cases of malaria were notified in the state of Amazonas. Among the factors that associate malaria and indigenous peoples, the most significant were sex, children and high levels of parasitemia. The magnitude of Plasmodium vivax infection is higher than Plasmodium falciparum, although this parasite was more frequent in indigenous than other races. In regards to mortality, 109 deaths were registered, most of them related to P. vivax.
CONCLUSION: The findings underscore the importance of look at indigenous people differently of other races. The associated factors highlight a profile of cases severity, because of highest parasitemia, many cases of P. falciparum although high frequency of P. vivax, and children. Furthermore, the mortality in indigenous, specially in older people is worrying.

Entities:  

Mesh:

Year:  2020        PMID: 33085704      PMCID: PMC7577477          DOI: 10.1371/journal.pone.0240741

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Malaria is a worldwide health problem, with the majority of cases occurring on the African continent (93%), followed by the Southeast Asian region (3.4%) and the Eastern Mediterranean region (2.1%). In 2018, it is estimated that there were 228 million cases of malaria worldwide, in comparison to 251 million cases in 2010, and 231 million cases in 2017. The incidence rate of malaria decreased globally between 2010 and 2018, from 71 to 57 cases per thousand at risk inhabitants [1]. Despite being avoidable and treatable, malaria continues to have a great impact on human health and its subsistence [1]. In the Americas, despite having a lower prevalence when compared to global levels, malaria is a severe problem. Three countries (Brazil, Colombia and Venezuela) account for 80% of all estimated cases in the Americas, which 51% of the cases occurred in Venezuela, followed by Brazil with 23% of the cases in 2018 [1]. In Brazil, the majority of cases (99%) are concentrated in the Amazon region, which is linked to environmental factors that favor the occurrence and transmission of malaria such as high temperatures, high precipitation and humidity, low altitude and its extensive network of rivers [2, 3]. Furthermore, environmental changes due to anthropic activity, especially Forest clearing, cause great impact on the malaria transmission. Such alterations favor vector breeding sites that, when combined with the population's lifestyle and its demographic and socioeconomic characteristics, impact on the occurrence of malaria. In this context, the indigenous population may be more vulnerable to malaria, due as much to the rural location of their homes as to their lifestyle [4]. The state of Amazonas reported more than 82,000 new cases of malaria in 2017 [5]. This state also has the highest proportional indigenous population in Brazil, as it has 183,514 indigenous inhabitants, which corresponds to 22.4% of the total of the country [6]. Although there are publications about malaria in the Amazon, information on malaria in indigenous populations is still poorly explored and reported in a generic manner [7-9]. Therefore, studies on the association between the occurrence of malaria and indigenous people, as well as the magnitude of the disease in this population, are necessary. The aim of this study was to the aim of this study was to identify factors associated with malaria in indigenous people, in a scenario of high malaria incidence in the state of Amazonas, Brazil, from 2007 to 2016.

Materials and methods

Study site and population

The study site is the state of Amazonas which, according to the 2010 Population Census, had a population of 3,483,985 inhabitants, in a total area of 1,559,161 km2 and is comprised of 62 municipalities [10]. Amazonas is the Brazilian state with the most proportion of indigenous population (22.4%). Brazil counts 444,747 indigenous people, of which 88,299 are in the state of Amazonas, and 70% live on indigenous lands. There are 2344 indigenous villages (aldeias) and 220 ethnic groups in the state of Amazonas. The National Malaria Control Program in Brazil relies on the early diagnosis and treatment of malaria cases, whose infection is detected by microscopy. The treatment policy for uncomplicated malaria: infections by P. vivax or P. malariae is chloroquine in 3 days and primaquine in 7 days; infections by P. falciparum, the association of artemeter with lumefantrine is used [2]. As a demonstration of continued surveillance efforts to establish a process of expanding the supply of timeliness of diagnosis and treatment, regardless of the extensive network of malaria laboratories available throughout the Brazilian Amazon (3,492 laboratories and 48,849 healthcare professionals across the state of Amazonas network) [3], the use of Rapid Diagnostic Tests (RDT) is being encouraged in Brazil, especially in remote areas, where there is less access to microscopy facilities [2]. The distribution and use of RDTs increased from 1486 tests in 2011 to 14,655 in 2015, and occurred principally in areas without good microscopy facilities [2, 3], despite this, highest number of passive malaria case detection are carried out. There is no difference in the indigenous malaria health program to the general population in Brazil. After diagnosis of malaria, treatment is immediately prescribed and administered free of charge to all the patients. This study uses the categories of race in regards to registered cases of malaria, as per the methodology of the Brazilian Institute of Geography and Statistics (IBGE) on self-reported race. However, the registration of this particular variable in the Epidemiological Surveillance Information System (SIVEP) was only mandatory from 2013 onwards, so an analysis of this nature needs to deal with missing data. From 2013 on, the following definitions were applied: Indigenous (Malaria in patients who identified themselves as indigenous): positive malaria cases in individuals who identified themselves as indigenous or those with indigenous villages as their likely place of infection, as reported on SIVEP. Other races (Non-indigenous): positive malaria cases involving white, black, yellow, brown-skinned patients or those who chose not to reply. No information regarding race (missing): cases in which the race variable was not filled in and cannot be automatically attributed because it was a case in which the place of probable infection was not the indigenous village.

Study design

Cross-sectional study of positive cases of malaria in the state of Amazonas, from 2007 to 2016, using secondary data from national surveillance system.

Ethical considerations

All ethical criteria related to Resolution 466/12 of the National Health Council were respected, especially regarding confidentiality and non-disclosure of information. This study was approved by the Ethics Review Board of the Federal University of Amazonas (Process Number 2,302,738—September 28, 2017), and requested a waiver of the Informed Consent Form, since it dealt with secondary data, systematically collected in the services and obtained without identifying the subjects.

Procedures and sources of data

Reports of new positive cases of malaria were obtained from the Malaria Epidemiological Surveillance Information System (SIVEP-Malaria), excluding relapsing cases and treatment failure. Malaria death statistics were obtained from the Mortality Information System (MIS). Only the cases of malaria in which the patients’ municipality of residence and infection report came from the state of Amazonas, and which occurred between January 1, 2007 and December 31, 2016 were considered. The Ministry of Health malaria case definition is: malaria suspect person whose presence of parasite or some of its components have been identified in the blood by laboratory examination. Therefore, out of a total of 1,055,852 notifications, only 936,379 cases were considered in this analysis. A total of 1,055,852 cases of malaria were reported between 2007 and 2016. Of these 119,473 (11.3%) were excluded due to lack of data, errors when registering the case or that slides registered just to review cured cases of those new cases already reported, which resulted in 936,379 cases analyzed. The completeness of the race variable was 40.2% throughout the period, which corresponded to 376,300 subjects with information on race. It is noteworthy that this variable was only mandatory from 2013 onwards, from whence onwards the completeness was 96.2% (2013–2016). We considered indigenous people those who were this way filled in the race variable. Cases without race information were reclassified for the purpose of this study. So, we considered indigenous race if there was no race data and the probable place of infection was the indigenous village. Thus, 42,702 subjects, who previously had missing information on race, received an indigenous classification based on this criterion. The option to use “probable place of infection = indigenous village” was a form of “multiple imputation”. This interpretation was assumed based on the guidelines of SIVEP which defines a village (known as aldeia in Portuguese) as a "cluster of indigenous areas include villages and huts". Therefore, it is assumed that the records that had village (aldeia) as a probable place of infection refer to the occurrence of malaria in indigenous populations, since they are characteristic of indigenous peoples' dwellings, and that the non-indigenous population would be included as little as possible. This methodology for imputing indigenous race has a low risk of bias, since a subject whose likely infection site is the "village" must be a local resident, and therefore, indigenous. On the other hand, there are health professionals who access the villages, however, being a case of malaria, it is more likely that the race information will be filled in, otherwise, it can also be considered that the quantity of health professionals is small face to the local indigenous population, causing no impact on this analysis.

Data analysis

The database was organized and analyzed using Stata software version 13. For morbidity analysis, the cases were stratified into indigenous, non-indigenous and those without information about their race. The analysis of deaths included the registration of race in the MIS, which stratified it into indigenous and non-indigenous, since completeness of the information was 100% for this last data source. In the descriptive phase, data were analyzed according to frequency and distribution, presenting categorical variables in percentages. For ordinal variables, the chi-square trend test was performed to verify the tendency of increases or reductions in proportions. P-value <0.01 was considered statistically significant. For multivariate analysis, stepwise logistic regression was used to identify factors associated with malaria, and controlled for the other variables in each stratum: indigenous, and non-indigenous. Those cases without data on their race were analyzed descriptively. In the modeling process the P-value significance criterion <0.20 was used to include the variables in the model, based on the bivariate analysis, and the variables with statistical significance, with P-value <0.05, were maintained in the final model. Association measures were calculated using crude and adjusted odds ratios (OR), together with their confidence intervals (95% CI). The fit of the model was evaluated by the Hosmer & Lemeshow test.

Variables

The variables used were extracted from the databases (SIVEP and MIS) and the completeness of each variable was calculated. The following variables were used: Spatial: zone, municipality of probable infection and residence, place of probable infection and residence; Demographics: sex (female and male); age group in years (<1, 1year of age <10, 10 years of age <20, 20 years of age <40, 40 years of age <60 and ≥60), race (indigenous, non-indigenous, no data on race) and schooling (years of study) (illiterate, 1–4 years of study, 5–9 years of study, ≥10 years of study); Clinical-Laboratory: microscope surveillance slide type: active case surveillance (health professionals look for cases). After notification of one or more cases of malaria and determination of the place of transmission, professionals perform active detection of other symptomatic or non-symptomatic cases; passive case surveillance (when the patient, usually with symptoms, seeks the notifying health service to be tested) Parasitic infection species: Plasmodium vivax; Plasmodium falciparum which included P. falciparum and P. falciparum + gametocytes of P. falciparum; Mixed infection by P. vivax + P. falciparum which included P. vivax + gametocytes of P. falciparum and P. falciparum + P. vivax; Other species which included infections caused by P.malariae and P. ovale. Parasitemia level in the positive cases (the number of parasites in thick smears) was graded using the plus system scale: <+/2 (less than one parasite per 100 thick film fields); +/2 (up to one parasite per 100 thick film fields); + (1 to 10 parasites per 100 thick film fields); ++ (11 to 100 parasites per 100 thick film fields); +++ (1 to 10 parasites per one thick film field); ++++ (>10 parasites per one thick film field); Treatment effectiveness: time between first symptoms and diagnosis (days); Time between first symptoms and treatment (days); and timeliness of treatment (relationship between date of diagnosis and date of start of treatment).

Results

Malaria cases were predominant in males in all categories, but in non indigenous people and missing race data this proportion was higher. In the indigenous category there was a predominance in the age group between 1 and 10 years of age, whose proportion decreases as age increases, while in non-indigenous and missing races groups the predominance occurred in the age range between 20 and <40 years of age. The low level of education was similar in both indigenous and non-indigenous groups, with higher proportions in individuals with only 1 to 4 years of schooling (Table 1).
Table 1

Characterization of malaria cases by location of probable infection, in indigenous patients (village or self-reported indigenous), non-indigenous and missing data on race.

Amazonas state, Brazil, 2007–2016.

Indigenous*Non-Indigenous**Missing data
VariablesN%n%n%
Sex (completeness: >99%)
Male9168054.3015159560.6031043660.00
Female7715045.709857539.402069440.00
Age group (years) (completeness: 100%)
< 145932.7229901.2073281.42
1 to < 106074735.985239320.9412221823.62
10 to < 204020923.826347225.3711747622.71
20 to < 404166324.688207632.8116844832.56
40 to < 60154279.143835415.338004015.47
60 or over389373.67108794.35218674.23
Schooling (years) (completeness: 59.2%)
Illiterate3804323.062626023.065695012.83
1 to 45057930.659583838.6614389832.41
5 to 92395114.526135724.7515219334.28
10 or more150559.123748215.12314387.08
Not applicable3737722.652694810.875954013.41
Type of surveillance slide (completeness: 100%)
Passive case surveillance8946052.9917217052.9936690870.92
Active case surveillance7937047.017800231.1815046929.08
Parasitemia level by plus system scale (completeness: 99.5%)
< +/2 (less than one parasite per 100 thick film fields)4164725.228091232.5113813926.70
+/2 (up to one parasite per 100 thick film fields)3211219.454174116.779197117.78
+ (1 to 10 parasites per 100 thick film fields)4006224.265370821.5811821622.85
++ (11 to 100 parasites per 100 thick film fields)4760728.836890427.6815732730.41
+++ (1 to 10 parasites per one thick film field)36002.1835631.43113992.20
++++ (>10 parasites per one thick film field)1040.06740.033220.06
Test results (completeness: 100%)
P. vivax14513285.9622953391.7544788486.57
P. falciparum2209813.09198117.926612312.78
Mixed infection15710.938140.3333660.65
Other290.02140.0140.00
Time between first symptoms and diagnosis (days)
03471320.563285313.1380033515.47
13508620.785676422.6911264521.77
23008317.825189920.7510005519.34
32110612.503777915.107949815.37
4 to 72575615.264417417.669675418.70
> 72207013.072667010.66483499.35
Time between first symptoms and treatment (days)
02906417.223002312.006391612.35
13432220.335557622.2210406920.12
23069418.185201520.799261117.90
32209713.093835015.337138913.80
4 to 72846116.864600318.398840217.09
> 72417814.322817311.269697018.74
Timeliness of treatment (hours)
≤ 487475944.2811256444.9925679149.63
    > 489407155.7213760855.0126058650.37

Source: Epidemiological Surveillance Information System for Malaria, data obtained January, 2018.

The total sample was 936,379 cases. The percentage is calculated in the column.

† Chi-square test for significant trend with P-value <0.01 for all variables, in Indigenous classification, Non-indigenous and those missing data on race.

* Indigenous is considered the combination of an individual with a declared indigenous race or having the village as a place of infection.

** Non-indigenous is the combination of all other races, excluding the indigenous race and missing data.

Characterization of malaria cases by location of probable infection, in indigenous patients (village or self-reported indigenous), non-indigenous and missing data on race.

Amazonas state, Brazil, 2007–2016. Source: Epidemiological Surveillance Information System for Malaria, data obtained January, 2018. The total sample was 936,379 cases. The percentage is calculated in the column. † Chi-square test for significant trend with P-value <0.01 for all variables, in Indigenous classification, Non-indigenous and those missing data on race. * Indigenous is considered the combination of an individual with a declared indigenous race or having the village as a place of infection. ** Non-indigenous is the combination of all other races, excluding the indigenous race and missing data. The passive case detection was more prevalent in all race categories. Parasitemia <+/2 (less than one parasite per 100 thick film fields) showed a higher percentage in the non-indigenous group; while parasitemia of ++ (11 to 100 parasites per 100 thick film fields) was higher among the indigenous group and in the cases where race was unspecified. In all racial groups, the main type of plasmodium was P. vivax, the predominant form of malaria in the region (Table 1). In all categories of race, there is a gradual decrease in the number of malaria cases as increases the number of days between the onset of symptoms and diagnosis. For the amount of time elapsed between the first symptoms and the beginning of treatment, the longest period observed in all categories was up to 2 days (Table 1). Regarding timeliness of treatment of malaria, the cases registered in all races categories (indigenous, non-indigenous and missing data groups) presented timely treatment longer than 48 hours: indigenous (55.7%), non-indigenous (55.0%) and those without data on race (50.3%) (Table 1). The result of logistic regression analysis in order to estimate the factors associated with indigenous malaria with the respective values of crude OR and adjusted OR is presented in Table 2. In this analysis, we excluded race missing data cases. Although we can see in the Table 1, this category is similar to non indigenous.
Table 2

Factors associated with malaria (crude and adjusted analysis), according to indigenous patients (village or self-reported indigenous) or non-indigenous.

Amazonas state, Brazil, 2007–2016.

VariablesIndigenous*
Crude ORCI 95%Adjusted ORIC 95%
Sex
Female1.01.0
Male0.770.76–0.780.830.82–0.84
Age group (years)
< 12.692.54–2.841.911.80–2.03
1 to < 102.031.97–2.111.621.56–1.68
10 to < 201.111.08–1.151.581.52–1.64
20 to < 400.890.62–0.921.341.29–1.39
40 to < 600.710.68–0.730.930.89–0.96
60 or over1.01.0
Schooling (years)
Illiterate1.041.02–1.071.311.28–1.35
1 to 40.380.37–0.390.470.46–0.48
5 to 90.280.27–0.290.380.36–0.39
10 or more0.290.28–0.300.40.41–0.44
Not applicable1.01.0
Type of surveillance slide
Passive case surveillance1.01.0
Active case surveillance1.961.93–1.981.731.70–1.75
Parasitemia level by plus system scale
(completeness: 99.5%)
<+/2 (less than one parasite per 100 thick film fields)1.01.0
+/2 (up to one parasite per 100 thick film fields)1.491.47–1.521.621.59–1.65
+ (1 to 10 parasites per 100 thick film fields)1.451.42–1.471.641.61–1.67
++ (11 to 100 parasites per 100 thick film fields)1.341.32–1.361.531.50–1.55
+++ (1 to 10 parasites per one thick film field)1.961.87–2.061.801.71–1.90
++++ (>10 parasites per one thick film field)2.732.03–3.682.101.53–2.88
Results of the test
P. vivax1.761.73–1.801.611.58–1.65
P. falciparum1.01.0
Mixed infection3.052.80–3.322.422.21–2.66
(P. falciparum + P.vivax)
Other**3.271.73–6.204.822.49–9.35
Timeliness of treatment (hours)
≤ 48h1.01.0
> 48h1.031.02–1.040.980.97–1.00

Source: Epidemiological Surveillance Information System for Malaria, data obtained January, 2018.

OR: odds ratio; 95% CI: 95% confidence interval.

Significance level <0.20 for simple logistic regression; Significance level <0.05 for multivariate logistic regression.

P-value was significant in all variables and categories.

*Indigenous classification is the combination of an individual with a declared indigenous status or having the indigenous village registered as the place where infection occurred.

** Other = P. ovale, P. falciparum + P. malariae or P. malariae.

Factors associated with malaria (crude and adjusted analysis), according to indigenous patients (village or self-reported indigenous) or non-indigenous.

Amazonas state, Brazil, 2007–2016. Source: Epidemiological Surveillance Information System for Malaria, data obtained January, 2018. OR: odds ratio; 95% CI: 95% confidence interval. Significance level <0.20 for simple logistic regression; Significance level <0.05 for multivariate logistic regression. P-value was significant in all variables and categories. *Indigenous classification is the combination of an individual with a declared indigenous status or having the indigenous village registered as the place where infection occurred. ** Other = P. ovale, P. falciparum + P. malariae or P. malariae. In the multivariate analysis, the following variables were associated to indigenous: male sex (OR = 0.83; CI 95%: 0.82–0.84); patients younger than 1 year in indigenous populations (OR = 1.91; CI 95%: 1.80–2.03), whose OR decreased as age increased, at least up to 40 years; education has greater magnitude among illiterates (OR = 1.31; CI 95%: 1.28–1.35), with reduction of OR as the education level increased; active case surveillance was strongly associated to indigenous malaria (OR = 1.73; CI 95%:1.70–1.75); the highest parasitemia (++++, i.e. >10 parasites 2.73 per one thick film field) is associated with malaria in the indigenous population (OR = 2.10; CI 95%:1.53–2.88); P. vivax, mixed infections (up to twice as many cases in indigenous patients) (OR = 2.42; CI 95%:2.2–2.66) and other, i.e., infections caused by P. malariae and P. ovale were 4 times more common in cases of malaria in the indigenous group (OR = 4.82; CI 95%: 2.49–9.35); timeliness of treatment, longer than 48 hours, appears as a malaria protective factor in indigenous (OR = 0.98; CI 95%: 0.97–1.00) (Table 2). Regarding malaria mortality in the period from 2007 to 2016, 109 deaths were reported (Table 3). Of these, two notifications were excluded due to lack of information or errors when filling in the forms. Considering indigenous groups, there were 34 deaths, 13 female and 21 male. Higher mortality levels were observed in those older than 60 years (32.3%). Regarding the non-indigenous group, there were 73 deaths, the highest number of deaths among female patients, and the most prevalent age group was between 20 and <40 years of age.
Table 3

Distribution of deaths caused by malaria, in indigenous and non-indigenous populations, Amazonas state, 2007 to 2016.

VariablesIndigenousNon-indigenous
n%n%
Sex
Female1338.244054.79
Male2161.763345.21
Age group (years)
< 1411.7634.11
1 to < 10617.651317.81
10 to < 20514.7156.85
20 to < 40514.712128.77
40 to < 6038.821216.44
60 years or over1132.351926.03
Underlying cause of death (ICD)
B509 –Malaria caused by Plasmodium falciparum with unspecified severity617.651419,18
B519 –Malaria caused by Plasmodium vivax without complications1235.292939.73
B54—Malaria caused by unidentified parasite926.471621.92
B518—Malaria caused by Plasmodium vivax with other complications411.761115.07
B500—Malaria caused by plasmodium falciparum with cerebral complications12.9434.11
B538 –Other types of malaria with parasitological confirmation, unclassified in other sections12.94-0.00
B508 –Other severe and complicated types of malaria caused by Plasmodium falciparum12.94-0.00

Source: Mortality Information System, data obtained in January, 2018.

ICD (International Statistical Classification of Health-Related Diseases and Problems).

Source: Mortality Information System, data obtained in January, 2018. ICD (International Statistical Classification of Health-Related Diseases and Problems). Both categories (Indigenous and Non-indigenous) had underlying cause of deathICD (International Statistical Classification of Health-Related Diseases and Problems) of death reported showing a greater proportion of P. vivax malaria.

Discussion

In the state of Amazonas, malaria is a disease that predominates in rural populations and reflects social and economic aspects that are accentuated in indigenous populations. Here the authors shed light on the factors associated with the occurrence of malaria in indigenous populations and cases that occurred in indigenous villages, as well as the description of the profile of deaths recorded by malaria in these populations in the state of Amazonas, by analyzing a period of 10 years (2007 to 2016). The predominance of malaria in indigenous males is similar to the results found in other studies conducted in the Amazon Region [2, 11–14], which justify such predominance based on indigenous behavior and a lifestyle based on extractivism and family farming, which is predominantly performed by men who consequently are more exposed to contact with the vector and the parasite [15, 16]. The highest proportion of cases among children up to 10 years old in indigenous peoples found in this study is equivalent to historical studies in the Amazon [17, 18]. In a riverine community in Portochuelo (Rondônia), a higher prevalence of malaria was found in children under 16 years of age [19]. Similar results were found in a study with the Yanomami tribe, on the border between Brazil and Venezuela, where children under 16 were the most affected by malaria [20]. In other studies, results were also found in younger age groups (children under 14 years old), such as schoolchildren and preschoolers [11, 21, 22]. The malaria treatment guideline envisages immediate malaria treatment (timeliness of treatment) to be provided to all patients with positive slide results or positive rapid test results for both symptomatic and asymptomatic cases [23]. This fact may be closely related to the high proportion of cases with time of up to 48 hours between onset of symptoms and time of diagnosis and/or treatment time of up to 48 hours in indigenous people. A study conducted in the state of Amazonas, with a non-indigenous population, showed that most patients were diagnosed predominantly within three days of symptom onset (94.3%). The timeliness of treatment diagnosis and treatment helps to prevent hospitalizations and deaths, but also help to control disease transmission by preventing or reducing the onset of parasite (gametocyte) sexual stages in human hosts, which are the infectious forms in the vectors [24]. Regarding the Plasmodium species, the present study showed similar results to those performed in non-indigenous populations, if we consider that P. vivax account for majority of the cases [25, 26]. An epidemiological malaria survey found prevalence of P. vivax cases, followed by P. falciparum and mixed infection cases (P. vivax + P. falciparum) [27]. It is necessary to remark that we found highest prevalence of P. falciparum and mixed infection in indigenous population, which cause more impact in the indigenous in terms of severity fo the disease. Maybe this aspect can explain that in indigenous we had more cases in the passive detection, which leads people to look for diagnosis faster because of the symptoms. In Brazil, the incidence of P. falciparum and P. vivax cases occurred at similar levels until 1988, after which the proportion of P. falciparum cases progressively decreased, while cases involving P. vivax increased and from then onwards became the predominant species responsible for over 90% of episodes of malaria [4, 5, 27]. It is important to note that there are biological differences between P. vivax and P. falciparum, which make P. vivax particularly challenging to control and eliminate in malaria endemic regions [28-30]. According to a study in Papua New Guinea, relapses may be the cause of about 80% of P. vivax cases [31]. A recent study in the state of Amazonas also suggests that relapses made a significant contribution to cases in this region [32]. The Timeliness of treatment found in this study can be interpreted as an effort to advance treatment initiation is due to the expansion of the laboratory network and the action of community health workers (CHA), which contributed to the decreasing trend observed in the percentage of malaria hospitalization of 3.3% in 1999 to 1.4% in 2009: a significant reduction of 79% [3]. The biggest obstacles to malaria treatment in indigenous populations is getting access to them due to the population dispersion and also the great distances involved as well as the local geography which both make the logistics of care more expensive. From the perspective of the diagnosis and treatment of malaria in indigenous peoples, the greatest difficulty is in reaching remote villages, due to the complexity of access which is only by river. The microscopy network does still not meet the total population coverage. The performance of well-trained and active indigenous health agents (IHAs) is a positive aspect for disease control [13]. In a study on factors associated with malaria treatment in the Brazilian Amazon, it was found that timeliness of treatment was associated with indigenous patients with low education (from zero to 5 years of schooling). These variables indicate vulnerable and highly dependent groups of the public Unified Health System (SUS) [23]. In endemic areas in Brazil, people are aware of the symptoms of malaria, and usually seek care early on in the clinical manifestations, which makes severe conditions uncommon. A survey conducted in the state of Acre, Brazil found that about 22% of patients sought care in less than 48 hours, while more than 70% of people looked for care less than four days from the onset of symptoms and most patients had malaria by P. vivax [33]. These are probably the explanations for finding only non-severe cases in this casuistry. This early search for diagnosis and treatment is also important to prevent people with protozoa in the peripheral circulation from acting as a source of infection for the disease transmitter, as proper treatment eliminates the blood parasite within a few days. This may shed light on the importance of timeliness of treatment and low mortality from malaria. The adjusted multivariate analysis showed male is a protective factor for indigenous people, which differs from general population. This finding deserve investigation, since malaria transmission is related to activities that promote contact with vector, we do not know what occurs with indigenous. Regarding age, the strength of the association of malaria in indigenous people is greater the smaller the age group. This fact corroborates another study in indigenous populations, in which the disease is associated with children [20]. On the other hand, it differs from other studies that detect a greater problem of malaria in the economically active population among non-indigenous people [23]. In the case of indigenous people, transmission may be intra- or peridomestic, where the vector is more likely to infect children, especially when they sleep. The educational level must be interpreted with caution, since the indigenous populations, as they live in areas far from urban centers, may have more difficulty in accessing school. Perhaps this explains the greater chance of being a case among the illiterate. The chance of malaria cases among indigenous people through the active case surveillance may result from the way in which indigenous health services are organized, in systematically promoting this active case surveillance. If we combine the interpretation with the timeliness of treatment, it is observed that even though the majority occurring within 48 hours, when it is more than 48h, it was a protective factor. Some explanation about the organization of malaria control actions in the Indigenous population can be found in a study on the municipality of São Gabriel da Cachoeira, which has the most indigenous people concentration in state of Amazonas [34]. The level of parasitemia can be an indicator of the severity of the disease among indigenous people, with greater strength of association in cases of highest parasitemia (++++). Still on gravity, the parasitic form has a stronger association for mixed infection (P. falciparum + P.vivax) and another parasitic form (P. ovale, P. falciparum + P. malariae or P. malariae), which reveals that indigenous people have particularities to be considered, since whereas in the state of Amazonas and in non-indigenous populations the predominance is of P. vivax. The malaria mortality must be a rare event since the diagnosis and the treatment is freely available, and the health professionals are conscious of the importance in the case finding and management. However the mortality analysis reveals the unfavorable outcome, specially in male and older people. The underlying cause of death was caused by P. vivax with no complications in both population groups, indigenous and non indigenous. One problem with P. vivax infection is the possibility of causing unfavorable and unmeasured outcome [9, 35]. The limitations of this study are mainly related to the use of secondary data itself. For example, the lack of information on job occupation or other variable proxy to socioeconomic status did not allow to include in the analysis in order to find a better model adjustment. However, it is not possible to control report, missing data or typing errors, and also the underreporting malaria cases. The last cited can be a minor problem, since it is a compulsory notification disease, and the treatment is just made available after case notification. To tackle with race missing data, we proposed this method of race data imputation, which revealed to be useful to conduct this analysis. However it is known that, ideally, the 100% of completeness must be the goal of malaria control program. Even considering the problems of malaria secondary data, we emphasize enhancing of the quality, its universal coverage in Brazil, the availability of great data amount and the possibility to work with indigenous data, with no need to go to field data collection, which in indigenous issues has other than costs implications. Despite these limitations, we judge that not compromise the findings. They are useful in understanding of the malaria peculiarities in the indigenous population, since we found differences in the associated factors. We also remark the importance of the completeness of secondary data, mainly the variable race, because it can reveals cases profile, cases inequalities and contribute for malaria control.

Conclusions

The study findings presented here have identified the factors associated with malaria in indigenous populations and in other races. Among indigenous people, the disease predominates in men of a younger age and who have high parasitemia. Because indigenous inhabit places that with difficult access and with few health resources, the disease is more often detected via active case surveillance. The border municipalities which have indigenous populations presented higher than average percentage of malaria cases. Evidently there is a clear need to work on actions related to the planning and execution of health care for these locations. Obviously neglected, indigenous people in the Amazon region are particularly affected by severe infectious diseases such as malaria, which adds an obstacle to both the quality of life of these populations and the advance of disease control and elimination in the region. The findings presented here clarify the malaria transmission profile in these populations, as well as their risk factors, generating evidence that supports decision-making by managers of the Malaria Control Programs in the Amazon Region.

Distribution of cases of malaria by municipality.

Amazonas state, Brazil, 2007 to 2016. (DOCX) Click here for additional data file. 18 Jun 2020 PONE-D-20-05382 Factors associated with malaria in indigenous populations: a retrospective study from 2007 to 2016 PLOS ONE Dear Dr. Gonçalves, Thank you for submitting your manuscript to PLOS ONE.  Your submission has now been peer-reviewed by three experts in the field and myself. I agree that the manuscript would benefit from being revised according to the suggestions following and encourage you to do so. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ============================== ACADEMIC EDITOR: Herein the authors aim to identify the factors related to malaria in indigenous people in Amazon sate, Brazil, from 2007 to 2016. To accomplish this, they did use the Brazillian Malaria Epidemiological Surveillance Information System and the Mortality Informative System. They found that sex, age, education level, malaria surveillance system, parasitemia level, plasmodium species, and time to treatment were strongly associated with malaria in the indigenous group. Overall the manuscript is well written and organized. But several pitfalls do exist regarding the methodology. General: Please rewrite the abstract as suggested by one of the reviewers Perform  language copyediting for the entire text Methods Provide sufficient details about the SIVEP, SIVEP-Malaria, and MIS. Similarly, contextualize the readers your study setting, specifically the nuances about the Amazon state, the tribal villages, the national malaria program guidelines. How community healthcare workers perform the diagnosis of malaria in indigenous people? Any surveillance underway? How did you handle missing data? Results Does the outcome and severity of malaria infection vary according to race? Could you present malaria incidence by year? Is there any variation of malaria incidence in indigenous people throughout the study period? Discussion Address the limitations of your findings considering the drawbacks of working with national epidemiological information systems ============================== Please submit your revised manuscript by Aug 02 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. 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The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: No Reviewer #3: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors chose an interesting subject, with few approaches on literature regarding indigenous malaria in Brazil, but needs some revision concerned the following aspects: 1) Developing the indigenous lifestyle that contributed to presented results 2) In Methodology the paragraph about including as indigenous people those which referred living in "aldeias" it was not clear the meaning of the sentence " The only possible cases of erroneous inclusion would be the small number of health professionals who access such places to provide indigenous health care. The authors should explain what they had on mind with this assumption. 3) In Methodology - Definition of active and passive case malaria surveillance should be provided in methodology 4) In Methodology - It should be well defined how many thick blood smears were considered to establish malaria diagnosis since "the number of parasites in thick smears was graded using the plus system scale:" 5) In Methodology - please provide the number and the data of the approval of the study by the Ethics Review Board of the Federal University of Amazonas. 6) The authors should provide percentages of some observed variables such as age, parasitemia to better charactherize their found results. 7) Necessity of reviewing table 1 concerning some variables that do not match the mentioned percentage on parenthesis; the absolute values of some variables do not reach 100%, being low or above this percentage. 8) Please, add in Fig 1 the percentages observed, instead of informing only colors in the polygons -dark and light blue, respectively to low and high percentages 9) To strength the discussion (and even the conclusion) about the biggest obstacles to malaria treatment in indigenous populations that is getting access to them due to their geographical location as well as their dispersion in the state of Amazon, authors should include a map with this information on the results 10) Based on the results, two topics in the conclusion need to be better addressed in the discussion - the reason why indigenous peoples of the state of the Amazon is "obviously" neglected and the significant predominance of passive case malaria diagnosis. Reviewer #2: The authors present malaria burden in the Amazonas in the last decade and identify the factors associated with it. However, the authors need to address certain points before the manuscript is suitable for publication. Page 4 1. Data of cross-sectional studies needs further explanations (how data was collected, target population, ACD vs PCD...). This is a key aspect that requires visibility in the manuscript. 2. A paragraph explaining a socio-economic description of the state of Amazonas (race distribution, wealth), and the epidemiology of malaria in the state is missing (access to malaria prevention, first-line treatment, vivax vs falciparum, ...). Page 5: 3. Which diagnostic test was used for confirmation of malaria? Was it performed at health facility or actively in the community? If only microscopy was used it must be stated as limitation in the paragraph were low RDT usage is discussed. 4. Expand the multiple imputation methods in an appendix. Page 6: 5. Variables included: what about malaria prevention (ITNs and IRS), and women being pregnant? Do the authors think that missing to include these variables might have an impact on the results? 6. I understand that job occupation and wealth (or socio-economic status) were not collected. If not available, they need to be included in study limitations in the discussion. Page 7: 7. It is briefly discussed at the end of the manuscript, but did the authors address the issue of malaria relapses associated with P. vivax? If done, how were relapses excluded/differentiated? Page 8: 8. It is important that the authors clarify the terms active case detection and passive case detection in the methods, and include further interpretations in the discussion. Page 12: 9. The first two paragraphs can be combined to avoid repetition. Discussion section: 10. This section needs a limitation paragraph and address potential biases of the study. Reviewer #3: The aim of this study was to identify factors associated with malaria in indigenous people, in Amazonas state, Brazil. The study used secondary data obtained from the Brazilian malaria surveillance program. Some major comments and minor details that require further information or consideration: Abstract - There is no sentence about background, the first phrase is the objective without basic information of where, when, why. - The period is repeated in Methods and Results. - The study design is not described. - There is no information about both data systems are Brazilian systems. - The basic statistical analysis is not too important to describe in the abstract. Definitions or study local details or variables is more important than those. - The phrase: “This state has the highest proportion of indigenous peoples and malaria in Brazil” in the Results section is a result of the study or an information about the study site? If it is an information should be in the Method section or in Background. - There is no results about the factors cited as associated malaria and indigenous people (measures of association, 95% IC, p). - The conclusion is not in accordance with the results presented in the abstract. Introduction - There is no dot in the end of the second sentence. - In the sentence: “The production and transmission of malaria”, the “production of malaria” could be replaced by development or occurrence. - Page 4: last sentence: The sentence would better written as: The aim of this study was to identify factors associated with malaria in indigenous people. Methods - The order of the sub-sections could be changed to better understand the methodology. First of all, it is necessary to describe the study site, study population, study design and ethical considerations. After that, describe the procedures, the data analysis, the definitions of variables. - The study design did not mention the use of secondary data. - “Definitions” sub-section is related to “Study population”. - The Study location could have more detailed. For instance, how many tribes/villages (aldeias), how many malaria screenings sites, amount of the indigenous population. - The sentence “The database was organized and analyzed using Stata software version 13” could be relocated to Data analysis sub-section. - To make sense I suggest to better describe the procedures, step by step. First, from where the data were obtained, describe the surveillance systems in Brazil, the notification case form. Then, the selection of variables and definitions. Results -Page 8: 1st paragraph: “Therefore, cases without race information were reclassified for the purpose of this study. These were classified as indigenous when they had their indigenous race registered or because they were a case where the probable place of infection was the indigenous village. Thus, 42,702 subjects, who previously had missing information on race, received an indigenous classification based on this criterion.” If they had their indigenous race registered so they were not a case without race. Those sentences should be rewritten. First describe how indigenous was identified. Then, describe what you did in the situation of cases without race information. Those sentences could be relocated to Methods section. - Page 8: There are no results in second, third and fourth paragraphs. They are summary of results. Summary of results is better located in paragraphs of Discussion section to introduce the discussion of the results. In the Results section it is necessary write the results, reporting n as well as %, measures of association, 95% IC, p. If a descriptor is used in the sentence (e.g. "the largest percentage") include number and percentage in brackets (n=#, %). - Page 12: the first paragraph is different from the second paragraph. In the first one there is no result described, in the second one there are for some variables. - Page 12: second paragraph: is better to describe as variables associated with indigenous population, not as significant variables. - Page 12: second paragraph: some variables has results in brackets, some has not. Describe all. - Page 12: second paragraph: “parasitemia in plus system scale is higher in the last strata of the scale” does not make sense. What does represent? Describe as higher parasitemia is associated with malaria in indigenous population. - Table 2, page 14: describe “Other” Results of the Test, in the table legend, for example. Discussion - Page 16, last paragraph: about what results the paragraph is related? The paragraph could be relocated to Study location sub-section. - Page 17: “After diagnosis of malaria, treatment was immediately prescribed and administered free of charge to all the patients [25].” This statement is redundant. It could be relocated to Study location sub-section, to better illustrate the Brazilian malaria program. It is important to briefly comment about indigenous malaria health program, if is apart of Brazilian general health program or not. - Page 17: “Regarding the Plasmodium species, the present study showed similar results to those performed in non-indigenous populations, with predominance of P. vivax as an infectious agent [27, 28]. An epidemiological malaria survey found prevalence of P. vivax cases, followed by P. falciparum and mixed infection cases (P. vivax + P. falciparum) [29], a result similar to that found in our study.” About these affirmations, the results showed the prevalence of P. falciparum in indigenous population was 13.09% while the prevalence in non-indigenous was 7.92%. For mixed infection, the prevalence in indigenous population was 0.93% and non-indigenous was 0.33%. We know P. falciparum and mixed infection P.falciparum/P.vivax are different in terms of morbidity, mortality, costs etc. P. vivax is the predominant species in both population but there is a difference in the distribution of species and consequently likely in the burden of disease in the indigenous population. - There are no considerations about limitations of the study. - The factors identified as associated with malaria in indigenous populations (table 2) were not discussed in the Discussion section. - The results of table 3 were not discussed in the Discussion section. - Sometimes they describe “the state of Amazonas” and “Amazon” for the apparently the same place. General comments - Add line numbers in the document helps us to point the text. - I suggest the authors to follow the STROBE guidelines on reporting of observational studies. - It would benefit from additional editing for English language and for redaction. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. 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Your efforts during the process of revision are acknowledged and I hope you also are pleased with the final result. We appreciate being able to publish your work and look forward to seeing your paper online as soon as possible. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, José Moreira, MD, MSc Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed Reviewer #3: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: No ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: No Reviewer #3: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The manuscript fulfilled the recommendations we had suggested and it is accepted for publication in PLos One Reviewer #2: The authors have addressed the comments suggested. However, the article will highly benefit from an in-detail revision of the English grammar. Reviewer #3: The authors have adequately addressed my comments. Some one minor detail that require correction: Introduction - Please correct the last sentence: “The aim of this study was to The aim of this study was to...” ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No Reviewer #3: No Submitted filename: Review_14092020.pdf Click here for additional data file. 12 Oct 2020 PONE-D-20-05382R1 Factors associated with malaria in indigenous populations: a retrospective study from 2007 to 2016 Dear Dr. Gonçalves: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. José Moreira Academic Editor PLOS ONE
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Journal:  PLoS Med       Date:  2015-10-27       Impact factor: 11.069

10.  High proportions of asymptomatic and submicroscopic Plasmodium vivax infections in a peri-urban area of low transmission in the Brazilian Amazon.

Authors:  Anne C G Almeida; Andrea Kuehn; Arthur J M Castro; Sheila Vitor-Silva; Erick F G Figueiredo; Larissa W Brasil; Marcelo A M Brito; Vanderson S Sampaio; Quique Bassat; Ingrid Felger; Wanderli P Tadei; Wuelton M Monteiro; Ivo Mueller; Marcus V G Lacerda
Journal:  Parasit Vectors       Date:  2018-03-20       Impact factor: 3.876

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  4 in total

1.  Evaluating recurrent episodes of malaria incidence in Timika, Indonesia, through a Markovian multiple-state model.

Authors:  Novyan Lusiyana; Atina Ahdika
Journal:  Infect Dis Model       Date:  2022-06-06

2.  Changing transmission dynamics among migrant, indigenous and mining populations in a malaria hotspot in Northern Brazil: 2016 to 2020.

Authors:  Erica Anne Wetzler; Paola Marchesini; Leopoldo Villegas; Sara Canavati
Journal:  Malar J       Date:  2022-04-19       Impact factor: 3.469

3.  On multifactorial drivers for malaria rebound in Brazil: a spatio-temporal analysis.

Authors:  Mario J C Ayala; Leonardo S Bastos; Daniel A M Villela
Journal:  Malar J       Date:  2022-02-17       Impact factor: 2.979

4.  Molecular Analysis Reveals a High Diversity of Anopheline Mosquitoes in Yanomami Lands and the Pantanal Region of Brazil.

Authors:  Teresa Fernandes Silva-do-Nascimento; Jordi Sánchez-Ribas; Tatiane M P Oliveira; Brian Patrick Bourke; Joseli Oliveira-Ferreira; Maria Goreti Rosa-Freitas; Ricardo Lourenço-de-Oliveira; Mariana Marinho-E-Silva; Maycon Sebastião Alberto Santos Neves; Jan E Conn; Maria Anice Mureb Sallum
Journal:  Genes (Basel)       Date:  2021-12-16       Impact factor: 4.096

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