Detecting space-time clusters of dengue fever in Panama after adjusting for vector surveillance data

Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales.Long term surveillance of vectors and arboviruses is an integral aspect of disease prevention and control systems in countries affected by increasing risk. Yet, little effort has been made to adjust space-time risk estimation by integrating disease case counts with vector surveillance data, which may result in inaccurate risk projection when several vector species are present, and when little is known about their likely role in local transmission. Here, we integrate 13 years of dengue case surveillance and associated Aedes occurrence data across 462 localities in 63 districts to estimate the risk of infection in the Republic of Panama. Our exploratory space-time modelling approach detected the presence of five clusters, which varied by duration, relative risk, and spatial extent after incorporating vector species as covariates. The Ae. aegypti model contained the highest number of districts with more dengue cases than would be expected given baseline population levels, followed by the model accounting for both Ae. aegypti and Ae. albopictus. This implies that arbovirus case surveillance coupled with entomological surveillance can affect cluster detection and risk estimation, potentially improving efforts to understand outbreak dynamics at national scales

COVID-19 pandemic in Panama: lessons of the unique risks and research opportunities for Latin America

The Republic of Panama has the second most unequally distributed wealth in Central America, has recently entered the list of countries affected by the COVID-19 pandemic, and has one of the largest testing rate per inhabitant in the region and consequently the highest incidence rate of COVID-19, making it an ideal location to discuss potential scenarios for assessing epidemic preparedness, and to outline research opportunities in the Region of the Americas. We address two timely important questions: What are the unique risks of COVID-19 in Panama that could help other countries in the Region be better prepared? And what kind of scientific knowledge can Panama contribute to the regional and global study of COVID-19? This paper provides suggestions about how the research community could support local health authorities plan for different scenarios and decrease public anxiety. It also presents basic scientific opportunities about emerging pandemic pathogens towards promoting global health from the perspective of a middle income countryThe Republic of Panama has the second most unequally distributed wealth in Central America, has recently entered the list of countries affected by the COVID-19 pandemic, and has one of the largest testing rate per inhabitant in the region and consequently the highest incidence rate of COVID-19, making it an ideal location to discuss potential scenarios for assessing epidemic preparedness, and to outline research opportunities in the Region of the Americas. We address two timely important questions: What are the unique risks of COVID-19 in Panama that could help other countries in the Region be better prepared? And what kind of scientific knowledge can Panama contribute to the regional and global study of COVID-19? This paper provides suggestions about how the research community could support local health authorities plan for different scenarios and decrease public anxiety. It also presents basic scientific opportunities about emerging pandemic pathogens towards promoting global health from the perspective of a middle income countr

Maternal invasion history of <i>Aedes aegypti</i> and <i>Aedes albopictus</i> into the Isthmus of Panama: Implications for the control of emergent viral disease agents

<div><p>Despite an increase in dengue outbreaks and the arrival of chikungunya and Zika disease in Panama, studies on the demographic history of the invasive <i>Aedes</i> mosquitoes that are the principle vectors of these diseases are still lacking in this region. Here, we assess the genetic diversity of these mosquitoes in order to decipher their invasion histories into the Isthmus of Panama. DNA sequences from the mitochondrial cytochrome C oxidase I gene obtained from 30 localities in 10 provinces confirmed the presence of more than one mitochondrial haplogroup (i.e., maternal lineage) in each species. The invasion of <i>Aedes albopictus</i> was likely from temperate European countries, as the most frequent and widespread haplogroup in Panama harbored variants that are uncommon elsewhere in the Americas. Two infrequent and geographically restricted <i>Ae</i>. <i>albopictus</i> haplotypes appear to have subsequently invaded Panama from neighboring Costa Rica and the USA, respectively. In addition, we recovered two deeply divergent mitochondrial clades in Panamanian <i>Aedes aegypti</i>. The geographic origins of these clades is unknown, given that divergence in the mitochondrial genome is probably due to ancient population processes within the native range of <i>Ae</i>. <i>aegypti</i>, rather than due to its global expansion out of Africa. However, Panamanian <i>Ae</i>. <i>aegypti</i> mitochondrial sequences within the first clade were closely related to others from Colombia, Bolivia, Brazil, Mexico and the USA, suggesting two separate invasions from Western Hemisphere source populations. The pattern of increased genetic diversity in <i>Aedes</i> mosquitoes in Panama is likely facilitated by the numerous land and water inter-connections across the country, which allows them to enter via sea- and land-transportation from Europe, North, Central and South America. Our results here should be considered in disease mitigation programs if emergent arboviruses are to be effectively diminished in Panama through vector suppression.</p></div

Maternal invasion history of <i>Aedes aegypti</i> and <i>Aedes albopictus</i> into the Isthmus of Panama: Implications for the control of emergent viral disease agents - Fig 2

<p><b>(A) Neighbor-joining phylogenetic tree of Panamanian and worldwide CO1 haplotypes of <i>Aedes aegypti</i> from GenBank</b> (<a href="http://blast.ncbi.nlm.nih.gov/" target="_blank">http://blast.ncbi.nlm.nih.gov/</a>). Panamanian haplotypes belonging to sub-Clade A (a), sub-Clade A (b) and Clade B are shown in green, red and blue triangles, respectively. Bootstrap values depicting branch support higher than 60% are shown in the tree. Asterisks (*) in Haplotype 1 and Haplotype 13 indicate most frequent Panamanian haplotypes within sub-Clade A (b) and Clade B, respectively. <b>(B) TCS network depicting mutational relationships among three CO1 haplogroups of <i>Aedes aegypti</i>.</b> Haplogroups 1, 2 and 3 mimic the color of sub-Clade A (b), Clade B and sub-Clade A (a), in that order. Haplotypes are represented by circles and their sizes reflect their population frequencies. Missing haplotypes are represented by blue and green dots and numbers along lines are mutational differences. Haplogroups 1, 2 and 3 match those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194874#pone.0194874.t003" target="_blank">Table 3</a>. <b>(C) Geographic distribution of haplogroups 1 (red), 2 (blue) and 3 (green) across Panama.</b> Bars correspond to the regional frequency of that haplogroup per sampling Province (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194874#pone.0194874.t001" target="_blank">Table 1</a> for additional details). Black diamond (i.e., North arrow) indicates the direction to the geographic North Pole.</p

Heat map depicting the geographic distribution and frequency of <i>CO1</i> haplotypes of three haplogroups of <i>Ae</i>. <i>aegypti</i> and three haplogroups of <i>Ae</i>. <i>albopictus</i> found in Panama.

<p>Heat map depicting the geographic distribution and frequency of <i>CO1</i> haplotypes of three haplogroups of <i>Ae</i>. <i>aegypti</i> and three haplogroups of <i>Ae</i>. <i>albopictus</i> found in Panama.</p

Intra-population diversity metrics for <i>Ae</i>. <i>aegypti</i> and <i>Ae</i>. <i>albopictus</i> from 10 Provinces of Panama, based on analyses with molecular sequences of the <i>CO1</i> gene.

<p>Intra-population diversity metrics for <i>Ae</i>. <i>aegypti</i> and <i>Ae</i>. <i>albopictus</i> from 10 Provinces of Panama, based on analyses with molecular sequences of the <i>CO1</i> gene.</p

Maternal invasion history of <i>Aedes aegypti</i> and <i>Aedes albopictus</i> into the Isthmus of Panama: Implications for the control of emergent viral disease agents - Fig 3

<p><b>(A) Neighbor-joining phylogenetic tree of Panamanian and worldwide <i>CO1</i> haplotypes of <i>Aedes albopictus</i> from GenBank</b> (<a href="http://blast.ncbi.nlm.nih.gov/" target="_blank">http://blast.ncbi.nlm.nih.gov/</a>). Panamanian haplotypes belonging to Clade A, sub-Clade B (b) and sub-Clade B (c) are shown in red, brown and green triangles, respectively. Bootstrap values depicting branch support higher than 60% are shown in the tree. Asterisks (*) in Haplotypes 1, 4 and 3 indicate most frequent Panamanian haplotypes in Clade A, sub-Clade B (b) and sub-Clade B (c), respectively. Black diamond symbolizes sequence AB907801 that was found in Costa Rica and Western Panama. <b>(B) TCS network depicting mutational relationships among three <i>CO1</i> haplogroups of <i>Aedes albopictus</i>.</b> Haplogroups 1, 2 and 3 mimic the color of Clade A, sub-Clade B (c) and sub-Clade B (b), in that order. Haplotypes are represented by circles and their sizes reflect their population frequencies. One missing haplotype is represented by a red dot in haplogroup 1 and numbers along lines are mutational differences. Haplogroups 1, 2 and 3 match those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194874#pone.0194874.t003" target="_blank">Table 3</a>. <b>(C) Geographic distribution of haplogroups 1 (red), 2 (green) and 3 (brown) across Panama.</b> Bars correspond to the regional frequency of that haplogroup per sampling Province (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0194874#pone.0194874.t001" target="_blank">Table 1</a> for additional details). Black diamond (i.e., North arrow) indicates the direction to the geographic North Pole.</p

Maternal invasion history of <i>Aedes aegypti</i> and <i>Aedes albopictus</i> into the Isthmus of Panama: Implications for the control of emergent viral disease agents - Fig 1

<p><b>Map (A) depicts <i>Aedes</i> collection localities from Panama</b>. Localities (numbers in red), provinces (codes in red), and <i>comarcas</i> (codes in black; a <i>comarca</i> is an indigenous political region). Each province and comarca is labeled. BOC = Bocas del Toro; CHI = Chiriquí, CNB = Comarca Ngobe-Buglé, VER = Veraguas; HER = Herrera; LOS = Los Santos; COC = Coclé, COL = Colón; PAE = Panamá Este; PAO = Panamá Oeste; CKY = Comarca Kuna Yala; CKM = Comarca Kuna de Madungandí; CKW = Comarca Kuna de Wargandí, CEM = Comarca Embera Wounaan; DAR = Darién. CKM is a territory within PAN province; CKW is a territory within DAR province. <b>Maps (B), (C) and (D)</b> depict collection site (circles in red) in relation to Precipitation, Population Density and Landscape use in Panamá, respectively. The dark lines in maps B, C and D represent the main roads across the country.</p

Localities, Counties and Provinces where <i>Aedes</i> mosquitoes were sampled in Panama, plus their geographic coordinates and relative species numbers.

<p>Localities, Counties and Provinces where <i>Aedes</i> mosquitoes were sampled in Panama, plus their geographic coordinates and relative species numbers.</p