Cross-border malaria in Northern Brazil

Cross-border malaria is a major barrier to elimination efforts [1]. It can be of two types. First, transnational malaria, defined as an internationally imported case to a location not within a border area (sending and receiving countries may or may not be adjacent). Second, border malaria, defined as an internationally imported case across or along borders between countries sharing a land border (the border region can extend up through the adjacent administrative areas along the international border, or up to a specified distance from an international border) [2]. As cross-border malaria cannot be solved unilaterally, many cross-country collaborations have been established to enhance surveillance and control at borders [3, 4]. Yet, those collaborations may be difficult or impracticable when countries differ widely in their progress and commitment toward malaria elimination when one of the countries faces civil or political unrest, and when national protocols for diagnosis, treatment, and control are distinct [1].

Cross-border malaria presents many challenges, such as the remoteness of border regions, often with limited access to health services; the varied nature of population mobility (seasonal, illegal, driven by economic opportunities, or resulting from a humanitarian crisis); the difficulty in devising surveillance systems for mobile populations; and the incomplete adherence to medication that can trigger drug resistance [2]. Countries close to malaria elimination may have the last remaining cases occurring along international borders (e.g., Bhutan and India), and cross-border malaria is often a threat to countries that have eliminated malaria (e.g., the resurgence in Costa Rica and Swaziland) [1] or are close to elimination (e.g., Suriname [5, 6]).

In the Americas, malaria epidemiology has seen major changes in the past two decades. From 2000 to 2015, malaria cases declined 61.2% in Latin America, Brazil launched a Plasmodium falciparum elimination plan in 2015 [7], Paraguay and Argentina were certified malaria-free in 2018 and 2019, respectively [8], and El Salvador has reported zero indigenous cases since 2017 and in 2020 applied for malaria-free certification [9, 10]. However, during the same period, malaria cases increased by 359% in Venezuela and reached 411,586 in 2017 (53% of the cases in the Americas) [11‐13]. After recording the lowest level in 36 years in 2016, malaria cases increased by 56.9% in Brazil in 2017 and again by 2.21% in 2018 [7]. In Guyana, malaria cases increased 25.5% in the same period, though the total number of confirmed cases annually remains under 15,000 [14].

This evolving epidemiology in the Americas brought attention to cross-border malaria along the Venezuela-Brazil-Guyana border. Following political changes that started in 2013, and an economic crisis that escalated starting in 2016, Venezuela faced major challenges, including in healthcare, and protests erupted. It is estimated that 4.6 million people had fled Venezuela by later 2020 [15]. The crisis also fueled an onrush of migrants to gold mines in Bolivar State (bordering Brazil, and where 70–80% of malaria cases are concentrated), boosting incidence locally [13], followed by a spillover to other areas in Venezuela and across international borders. Guyana, where artemisinin resistance is suspected to be emerging [16], has been a hotspot for illegal gold-mining, and economic activity that has been historically associated with human migration and malaria transmission in the Amazon. The type of gold extraction in the region contributes to the creation of puddles of stagnant water that favour mosquito breeding [17‐21]. Reduced access to diagnosis, poor quality treatment, and minimal protection against mosquito biting has increased the vulnerability of miners to malaria. Therefore, the Venezuela-Brazil-Guyana border witnesses intense human mobility fueled primarily by a humanitarian crisis and illegal gold mining activities.

Roraima, a Brazilian state situated between Venezuela and Guyana, bears the greatest burden among Brazilian states [22]. Since the beginning of 2016, cross-border cases imported into Roraima have increased to nearly 500 infections per month, from less than 100 in 2015. Two municipalities in Roraima, namely Boa Vista (the capital) and Pacaraima (bordering Venezuela), have recorded more than half of all cross-border malaria cases into Brazil between 2007 and 2018. Major concerns emerged among cases imported from French Guiana [20], Suriname [6], Guyana [7, 12], and Venezuela [13, 23, 24].

This study is a comprehensive overview of the current cross-border malaria epidemiology in Northern Brazil, specifically along the Venezuela and Guyana borders, considering the years 2007 to 2018. Spatial and temporal patterns in both border and transnational malaria are characterized, contrasting demographic and epidemiological profiles of malaria importation from Guyana and Venezuela.

Between 2007 and 2016, the number of malaria cases reported in Brazil dropped 72.9%; the decline for autochthonous cases was 73.4%, and for cross-border cases it was 47.6% (Table 1). However, between 2016 and 2018, autochthonous and cross-border cases increased by 60.9% and 147.0%, respectively. While cross-border cases represented, on average, around 3% of all reported cases in Brazil, the origin of those cases changed between 2007 and 2018, and four issues stand out (Table 1, Fig. 1). First, less than 1% of cross-border cases originate in countries that do not share a border with the Brazilian Amazon. Second, about 41% of the cross-border cases, on average, were border cases, and thus were reported in Brazilian municipalities that share an international border. Third, the majority of cross-border cases originated from French Guiana in the first half of the study period (2007–2012), with a peak of 68% in 2007, while Venezuela was the main source in the second half of the period (2013–2018), with a peak of 75% in 2018. Fourth, considering the types of cross-border malaria (i) French Guiana was the most important source of both border and transnational cases between 2007 to 2011, (ii) the majority of border cases between 2012 and 2015 originated from Peru, (iii) Guyana was the main source of transnational cases from 2012 to 2014, and (iv) Venezuela was the origin of the majority of border and transnational cases from 2016 to 2018 (in 2018, 67% and 84% of transnational and border malaria cases, respectively, originated from Venezuela). Roraima state was the recipient of most cross-border cases (70.7%), especially those originating from Venezuela (91.4%) and Guyana (67%). Among cross-border cases from Venezuela, 50.1% were notified in border municipalities, against only 4.8% of those from Guyana.

Among states in the Brazilian Amazon that share an international border, the percentage contribution of cross-border malaria cases among all cases reported varied spatially and temporally. Between 2007 and 2018, Roraima had the highest share of cross-border cases among all malaria cases reported in the state, while in Amapá the contribution never surpassed 1% (Fig. 2). However, during the same period, the distribution of autochthonous (Fig. 3a) and cross-border (Fig. 3b) cases largely varied by municipality.

Considering the years 2016 and 2018, characteristics of autochthonous and cross-border border malaria cases showed statistically significant differences (Table 2). The number of Venezuelan citizens infected abroad was more than 200 times the number of those infected in Brazil. Mining was by far the dominant occupation among cross-border cases, while agriculture was the most common among autochthonous cases. The age distribution of autochthonous and cross-border cases showed distinct patterns (Fig. 4a). Autochthonous cases peaked early, had a median age of 21 years, and consistently declined across adult ages. Cross-border cases had a delayed pattern, with a median age of 30, and two peaks: a small one at young children’s ages, and a more pronounced one around age 30.

Similarly, cross-border cases originating from Venezuela, Guyana, and other countries differed in the composition of every categorical variable that was analysed (Table 2). An important difference was in the nationality of cases: 98.9% of cross-border cases originating from Guyana were Brazilian nationals, while slightly over half (53.8%) originating from Venezuela were Brazilians. The type of occupation of most cross-border cases from Venezuela and Guyana was mining, while less than a third of cases originating in other countries declared this type of activity. With regards to parasite type, 75.2% of all cross-border cases were P. vivax, which is lower than the share of P. vivax among all malaria cases recorded in Brazil during the same period, 89.02%. Of the cross-border cases originating from Venezuela and Guyana, the percentage of P. falciparum cases were, respectively, 18.9% and 12.4%. Most cross-border malaria cases were passively detected (95.3%). With regards to age, 66.6% of cross-border cases were between 16 and 40 years; 73.8% of those originating from Guyana were in that age range. Also, 8.4% of the cross-border cases from Venezuela had ages under 15 years, against only 3.3% of those from Guyana (Fig. 4b).

Characteristics of malaria cases also varied by type of cross-border case, considering Venezuela and Guyana aggregated from 2016 to 2018 (Table 3). In the case of Venezuela, three important issues stand out. First, most transnational cases (95.6%) were Brazilians, while 87.8% of the border cases were Venezuelans. Second, 81.2% of border cases were individuals working on mining activities, against 65.8% of the transnational cases. Third, while the share of P. vivax cases was similar, 21.2% and 16.7% of the border and transnational cases, respectively, were P. falciparum. Among cross-border cases from Guyana, two distinctions are important. First, and in contrast with Venezuela, working on mining was more prevalent among transnational cases from Guyana (78.8%, against 55.3% in border cases). Second, 18.1% of border cases originating from Guyana were detected via active surveillance, a higher percentage than transnational cases (3.9%). Comparatively, 1% of the border cases and 2.6% of transnational cases with infections originating from Venezuela were diagnosed through active case detection.

There were 58,532 cases of malaria notified in the state of Roraima between 2016 and 2018. Of these, 14,467 were cross-border cases (99.7% from Venezuela and Guyana). Table 4 shows the results of the multivariable model. All variables, except The P. falciparum category, and the interactions between Guyanese nationality and the border indicator were statistically significant with p < 0.05. Guyanese and Venezuelan nationals had a 49.03-fold (95% CI: 7.95, 302.20) and 233.76-fold (95% CI: 109.41, 499.43) odds of being an imported case, respectively, as compared to individuals of Brazilian nationality. The estimate for cases with nationalities other than these three as compared to Brazil was high, but unstable and not statistically significant. Cases notifying in border municipalities had 0.56-fold (95% CI: 0.50, 0.62) odds of being imported as compared to transnational municipalities. However, the fitted interaction term demonstrates that among cases notifying at the border, imported cases have a 9.48-fold higher odds of being Venezuelan nationals as compared to cases notifying transnationally, above their baseline estimate of 233.76.

Other variables associated with an increased odds of being an imported case were being between the ages of 16 and 64, being infected with P. falciparum, and having either forestry, mining, tourism, or travelling as an occupation. Variables associated with decreased odds of being an imported case were being between the ages of 5 and 15 or 65 + , being infected with P. vivax, and working in agriculture, living domestically, or being either a hunter or fisherman.

This study comprehensively analysed the spatial and temporal dynamics of cross-border malaria in northern Brazil, particularly along the Brazil-Venezuela-Guyana border, and identified the correlates of cross-border cases in Roraima. Results show that cross-border cases from Venezuela and Guyana made up the majority of border and transnational cases since 2012, and that Roraima has remained the largest receiving state for cross-border cases over this period. There were significant differences in the profiles of cross-border and autochthonous cases as well as border and transnational cases originating from Venezuela and Guyana.

The results of this study bring about four important points relevant to malaria control and elimination in Brazil. First, border areas are highly vulnerable to remaining malaria hotspots despite country-wide elimination efforts. Since 2016, cross-border cases in the state of Roraima have been on the rise, mainly originating in Venezuela and Guyana. Within the state of Roraima, border municipalities tend to be isolated, with weaker surveillance and treatment capabilities than more internal municipalities [2, 22]. While active case detection is higher in border municipalities, the share of cases actively detected is still quite low. Also, civil strife and humanitarian crisis, resulting in moment across international borders, may happen suddenly. In the state of Roraima, cases imported from Venezuela increased quickly in a short period as the crisis in the country intensified [13, 22, 29]. The combination of limited resources and governance, unpredictable mobility, and some economic activities (such as mining) situate border regions as areas vulnerable to outbreaks of malaria that may challenge country-wide elimination efforts. This is true for other diseases; in 2018 Roraima reported over 300 measles cases (a disease that had been eliminated), traced back to predominantly Venezuelan migrants [22, 30]. The example of measles demonstrates the fragility of sustained disease elimination in Brazil’s border regions and illuminates the importance of understanding dynamics at the border and stratifying interventions accordingly [31].

Second, these results demonstrate the importance of recognizing vulnerable border areas and implementing surveillance as an intervention in line with the World Health Organization (WHO) Global Technical Strategy for malaria [32]. The third pillar of the WHO Global Technical Strategy for malaria 2016–2030 focuses on strengthening surveillance efforts to become a core intervention, as data collection and detection of cases is of paramount importance when planning the stratification of control efforts and resource distribution. Data-driven approaches to malaria stratification, particularly those that include cross-country collaboration with intense surveillance, are effective in combatting cross-border malaria [33‐35], although cross-country collaboration may be impracticable in some cases due to incongruent surveillance efforts or poor international relations across country borders [4]. Genetic and molecular techniques have the potential to monitor drug-resistant malaria parasites entering from neighboring countries [36]. This is particularly important as artemisinin resistance is suspected in Guyana [37, 38]. Implementation of genetic and molecular screening techniques in regions of the world with the infrastructure and economic capabilities of scaling these methods has proven invaluable when transmission is low and elimination is in sight [39‐41]. These methods may prove useful in certain contexts within the Brazilian Amazon, particularly in the state of Roraima, for the monitoring of drug resistance.

Third, the importance of understanding the profiles of different types of cross-border malaria cases was demonstrated. As opposed to the Venezuelan case, most of the cross-border malaria cases originating in Guyana are Brazilians who cross the border back-and-forth to work on gold mining. This dynamic is supported in the literature, and the results from this study corroborate the importance of Boa Vista as a hub for mobile mining populations seeking medical care [42]. Ultimately, the response to cross-border cases is inextricably linked to the demographic profiles of each population. For example, Venezuelan migrants seeking medical care and refuge in Brazil may be more likely to remain in the Brazilian Amazon if they receive refugee status [13, 22, 29]. Strengthening surveillance at the border among Venezuelan migrants, as well as treatment capacity along common routes of travel for these groups, contrast the need for targeted care, prophylactic measures, and active surveillance of Brazilian miners working in Guyana and seeking care in Boa Vista.

Two distinct movement patterns of cross-border cases travelling from Venezuela and Guyana into Roraima were hypothesized (Fig. 5). In the case of Venezuela (Fig. 5a), individuals fleeing the country cross the border into Roraima, making their first point of contact in the municipality of Pacaraima [22]. While many may settle there, others seek better conditions or apply for refugee status, eventually getting settled in other municipalities in Brazil [43]. In the case of Guyana (Fig. 5b), cross-border cases are predominantly Brazilian nationals travelling for economic opportunity (mainly gold mining, mostly illegal) [44]. These movements are likely to occur repeatedly and present a challenge to both Brazil and Guyana [42, 44]. In Guyana, 94% of malaria cases reported occurred in major gold mining regions, and the malaria scenario in Venezuela demonstrates the potential for small, isolated, malaria-dense populations with minimal resources to spur outbreaks of the disease and reverse progress toward elimination.

Fourth, the isolation of border regions and caseloads depending on two country’s malaria policies rather than one present major challenges for the implementation of control measures. The border of Roraima with Venezuela and Guyana are forested and porous. The potential for these regions to sustain malaria control without the ability to directly target at-risk populations may come from the introduction of novel interventions. Currently, Brazilians mining in Guyana travel back to Boa Vista to seek health care. Prophylactic interventions and more readily accessible treatment can be distributed far closer to gold mining sites, allowing individuals to increase economic productivity while preventing further infections and risk of cross-border cases. Malakit, a personal prophylactic and treatment kit, is one such example of an intervention that brings necessary services closer to the at-risk populations [45]. The borders of Venezuela and Guyana may be locations where interventions like Malakit, coupled with widespread active surveillance, could be highly effective. However, maximizing the efficiency and utility of this intervention will depend on knowledge of specific travel routes taken between neighbouring countries by high-risk individuals. Furthermore, efficacy will depend on neighbouring countries’ ability to collaborate. If efforts to curb malaria transmission are uneven across international borders, malaria elimination efforts are threatened [2].

This study has some limitations. Asymptomatic malaria infections are largely not captured by the NMCP in Brazil (similar to other countries), as individuals without symptoms do not seek medical care. Also, foreigners may report their nationality incorrectly (as Brazilians) when they seek medical care. Both limitations imply that these study results could be an underestimation of cross-border cases. Yet, data utilized in the analysis are the most comprehensive available.