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109. Longitudinal analysis of naturally acquired PfEMP1 CIDR domain variant antibodies identifies associations with malaria protection

Author

Obeng-Adjei, Nyamekye, primary, Larremore, Daniel B., additional, Turner, Louise, additional, Ongoiba, Aissata, additional, Li, Shanping, additional, Doumbo, Safiatou, additional, Yazew, Takele B., additional, Kayentao, Kassoum, additional, Miller, Louis H., additional, Traore, Boubacar, additional, Pierce, Susan K., additional, Buckee, Caroline O., additional, Lavstsen, Thomas, additional, Crompton, Peter D., additional, and Tran, Tuan M., additional

Published
2020
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115. Aggregated mobility data could help fight COVID-19

Author

Buckee, Caroline O., primary, Balsari, Satchit, additional, Chan, Jennifer, additional, Crosas, Mercè, additional, Dominici, Francesca, additional, Gasser, Urs, additional, Grad, Yonatan H., additional, Grenfell, Bryan, additional, Halloran, M. Elizabeth, additional, Kraemer, Moritz U. G., additional, Lipsitch, Marc, additional, Metcalf, C. Jessica E., additional, Meyers, Lauren Ancel, additional, Perkins, T. Alex, additional, Santillana, Mauricio, additional, Scarpino, Samuel V., additional, Viboud, Cecile, additional, Wesolowski, Amy, additional, and Schroeder, Andrew, additional

Published
2020
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116. Estimating internationally imported cases during the early COVID-19 pandemic

Author

Menkir, Tigist F., primary, Chin, Taylor, additional, Hay, James, additional, Surface, Erik D., additional, De Salazar, Pablo M., additional, Buckee, Caroline O., additional, Watts, Alexander, additional, Khan, Kamran, additional, Sherbo, Ryan, additional, Yan, Ada W. C., additional, Mina, Michael, additional, Lipsitch, Marc, additional, and Niehus, Rene, additional

Published
2020
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120. Longitudinal analysis of naturally acquired antibodies to PfEMP1 CIDR domain variants and their association with malaria protection

Author

Obeng-Adjei, Nyamekye, primary, Larremore, Daniel B., additional, Turner, Louise, additional, Ongoiba, Aissata, additional, Li, Shanping, additional, Doumbo, Safiatou, additional, Yazew, Takele B., additional, Kayentao, Kassoum, additional, Miller, Louis H., additional, Traore, Boubacar, additional, Pierce, Susan K., additional, Buckee, Caroline O., additional, Lavstsen, Thomas, additional, Crompton, Peter D., additional, and Tran, Tuan M., additional

Published
2020
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121. Plasmodium falciparum population genetic complexity influences transcriptional profile and immune recognition of highly related genotypic clusters

Author

Bei, Amy K., primary, Larremore, Daniel B., additional, Miura, Kazutoyo, additional, Diouf, Ababacar, additional, Baro, Nicholas K., additional, Daniels, Rachel F., additional, Griggs, Allison, additional, Moss, Eli L., additional, Neafsey, Daniel E., additional, Deme, Awa B., additional, Sy, Mouhamad, additional, Schaffner, Stephen, additional, Ahouidi, Ambroise D., additional, Ndiaye, Daouda, additional, Dieye, Tandakha, additional, Mboup, Souleymane, additional, Buckee, Caroline O., additional, Volkman, Sarah K., additional, Long, Carole A., additional, and Wirth, Dyann F., additional

Published
2020
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123. Human movement data for malaria control and elimination strategic planning

Author

Pindolia Deepa K, Garcia Andres J, Wesolowski Amy, Smith David L, Buckee Caroline O, Noor Abdisalan M, Snow Robert W, and Tatem Andrew J

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.

Published
2012
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128. Megacities as drivers of national outbreaks: the role of holiday travel in the spread of infectious diseases

Author

Mahmud, Ayesha S., primary, Kabir, Md. Iqbal, additional, Engø-Monsen, Kenth, additional, Tahmina, Sania, additional, Riaz, Baizid Khoorshid, additional, Hossain, Md. Akram, additional, Khanom, Fahmida, additional, Rahman, Md. Mujibor, additional, Rahman, Md. Khalilur, additional, Sharmin, Mehruba, additional, Hossain, Dewan Mashrur, additional, Yasmin, Shakila, additional, Ahmed, Md. Mokhtar, additional, Lusha, Mirza Afreen Fatima, additional, and Buckee, Caroline O., additional

Published
2019
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134. Estimating the probable cause of recurrence in Plasmodium vivax malaria: relapse, reinfection or recrudescence?

Author

Taylor, Aimee R, primary, Watson, James A, additional, Chu, Cindy S, additional, Puaprasert, Kanokpich, additional, Duanguppama, Jureeporn, additional, Day, Nicholas P J, additional, Nosten, Francois, additional, Neafsey, Daniel E, additional, Buckee, Caroline O, additional, Imwong, Mallika, additional, and White, Nicholas J, additional

Published
2018
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135. Multilocus haplotypes reveal variable levels of diversity and population structure of Plasmodium falciparum in Papua New Guinea, a region of intense perennial transmission

Author

Buckee Caroline O, Kiniboro Benson, Nale Joe, Senn Nicolas, Ntsuke Pilate O, Mueller Ivo, Wapling Johanna, Schultz Lee, Tavul Livingstone, Siba Peter M, Reeder John C, and Barry Alyssa E

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background The South West Pacific nation of Papua New Guinea has intense year round transmission of Plasmodium falciparum on the coast and in the low-lying inland areas. Local heterogeneity in the epidemiology of malaria suggests that parasites from multiple locations will need to be surveyed to define the population biology of P. falciparum in the region. This study describes the population genetics of P. falciparum in thirteen villages spread over four distinct catchment areas of Papua New Guinea. Methods Ten microsatellite loci were genotyped in 318 P. falciparum isolates from the parasite populations of two inland catchment areas, namely Wosera (number of villages (n) = 7) and Utu (n = 1) and; and two coastal catchments, Malala (n = 3) and Mugil (n = 3). Analysis of the resultant multilocus haplotypes was done at different spatial scales (2-336 km) to define the genetic diversity (allelic richness and expected heterozygosity), linkage disequilibrium and population structure throughout the study area. Results Although genetic diversity was high in all parasite populations, it was also variable with a lower allelic richness and expected heterozygosity for inland populations compared to those from the more accessible coast. This variability was not correlated with two proxy measures of transmission intensity, the infection prevalence and the proportion multiple infections. Random associations among the microsatellite loci were observed in all four catchments showing that a substantial degree of out-crossing occurs in the region. Moderate to very high levels of population structure were found but the amount of genetic differentiation (FST) did not correlate with geographic distance suggesting that parasite populations are fragmented. Population structure was also identified between villages within the Malala area, with the haplotypes of one parasite population clustering with the neighbouring catchment of Mugil. Conclusion The observed population genetics of P. falciparum in this region is likely to be a consequence of the high transmission intensity combined with the isolation of human and vector populations, especially those located inland and migration of parasites via human movement into coastal populations. The variable genetic diversity and population structure of P. falciparum has important implications for malaria control strategies and warrants further fine scale sampling throughout Papua New Guinea.

Published
2010
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136. The effects of a partitioned var gene repertoire of Plasmodium falciparum on antigenic diversity and the acquisition of clinical immunity

Author

Arinaminpathy Nimalan, Recker Mario, and Buckee Caroline O

Subjects
Arctic medicine. Tropical medicine, RC955-962, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Background The human malaria parasite Plasmodium falciparum exploits antigenic diversity and within-host antigenic variation to evade the host's immune system. Of particular importance are the highly polymorphic var genes that encode the family of cell surface antigens PfEMP1 (Plasmodium falciparum Erythrocyte Membrane Protein 1). It has recently been shown that in spite of their extreme diversity, however, these genes fall into distinct groups according to chromosomal location or sequence similarity, and that recombination may be confined within these groups. Methods This study presents a mathematical analysis of how recombination hierarchies affect diversity, and, by using simple stochastic simulations, investigates how intra- and inter-genic diversity influence the rate at which individuals acquire clinical immunity. Results The analysis demonstrates that the partitioning of the var gene repertoire has a limiting effect on the total diversity attainable through recombination and that the limiting effect is strongly influenced by the respective sizes of each of the partitions. Furthermore, by associating expression of one of the groups with severe malaria it is demonstrated how a small number of infections can be sufficient to protect against disease despite a seemingly limitless number of possible non-identical repertoires. Conclusion Recombination hierarchies within the var gene repertoire of P. falciparum have a severe effect on strain diversity and the process of acquiring immunity against clinical malaria. Future studies will show how the existence of these recombining groups can offer an evolutionary advantage in spite of their restriction on diversity.

Published
2008
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137. Disrupting Mosquito Reproduction and Parasite Development for Malaria Control

Author

Childs, Lauren M., Cai, Francisco Y., Kakani, Evdoxia G., Mitchell, Sara N., Paton, Douglas G., Gabrieli, Paolo, Buckee, Caroline O., Catteruccia, Flaminia, and Mathematics

Subjects
juvenile-hormone, culex-quinquefasciatus, anopheles-gambiae, parasitic diseases, aquatic stages, western kenya, population-dynamics, lepidoptera-noctuidae, plasmodium-falciparum, ecdysone agonists, insecticides
Abstract

The control of mosquito populations with insecticide treated bed nets and indoor residual sprays remains the cornerstone of malaria reduction and elimination programs. In light of widespread insecticide resistance in mosquitoes, however, alternative strategies for reducing transmission by the mosquito vector are urgently needed, including the identification of safe compounds that affect vectorial capacity via mechanisms that differ from fast-acting insecticides. Here, we show that compounds targeting steroid hormone signaling disrupt multiple biological processes that are key to the ability of mosquitoes to transmit malaria. When an agonist of the steroid hormone 20-hydroxyecdysone (20E) is applied to Anopheles gambiae females, which are the dominant malaria mosquito vector in Sub Saharan Africa, it substantially shortens lifespan, prevents insemination and egg production, and significantly blocks Plasmodium falciparum development, three components that are crucial to malaria transmission. Modeling the impact of these effects on Anopheles population dynamics and Plasmodium transmission predicts that disrupting steroid hormone signaling using 20E agonists would affect malaria transmission to a similar extent as insecticides. Manipulating 20E pathways therefore provides a powerful new approach to tackle malaria transmission by the mosquito vector, particularly in areas affected by the spread of insecticide resistance. COB, FYC and LMC were supported by Award Number U54GM088558 from the National Institute Of General Medical Sciences (NIGMS). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIGMS or the NIH. FC and SNM were partially supported by a NIH grant (grant ID: NIH 1R01A1104956-01A1), while FC, EGK, PG and DP were partially supported by the European Research Council FP7 ERC Starting Grant Anorep (grant ID: 260897) and by Harvard T. H. Chan School of Public Health funds. FC and DP were supported by the Bill & Melinda Gates Foundation (Grant ID: OPP1140143). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Published
2016

139. The geography of malaria elimination in Bangladesh: combining data layers to estimate the spatial spread of parasites

Author

Chang, Hsiao-Han, primary, Wesolowski, Amy, additional, Sinha, Ipsita, additional, Jacob, Christopher G, additional, Mahmud, Ayesha, additional, Uddin, Didar, additional, Zaman, Sazid Ibna, additional, Hossain, Md Amir, additional, Faiz, M Abul, additional, Ghose, Aniruddha, additional, Sayeed, Abdullah Abu, additional, Rahman, M Ridwanur, additional, Islam, Akramul, additional, Karim, Mohammad Jahirul, additional, Rezwan, M Kamar, additional, Shamsuzzaman, Abul Khair Mohammad, additional, Jhora, Sanya Tahmina, additional, Aktaruzzaman, M M, additional, Miotto, Olivo, additional, Engø-Monsen, Kenth, additional, Kwiatkowski, Dominic, additional, Maude, Richard J, additional, and Buckee, Caroline O, additional

Published
2018
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140. Nonannual seasonality of influenza-like illness in a tropical urban setting

Author

Lam, Ha Minh, primary, Wesolowski, Amy, additional, Hung, Nguyen Thanh, additional, Nguyen, Tran Dang, additional, Nhat, Nguyen Thi Duy, additional, Todd, Stacy, additional, Vinh, Dao Nguyen, additional, Vy, Nguyen Ha Thao, additional, Thao, Tran Thi Nhu, additional, Thanh, Nguyen Thi Le, additional, Tin, Phan Tri, additional, Minh, Ngo Ngoc Quang, additional, Bryant, Juliet E., additional, Buckee, Caroline O., additional, Ngoc, Tran Van, additional, Chau, Nguyen Van Vinh, additional, Thwaites, Guy E., additional, Farrar, Jeremy, additional, Tam, Dong Thi Hoai, additional, Vinh, Ha, additional, and Boni, Maciej F., additional

Published
2018
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142. Mortality in Puerto Rico after Hurricane Maria

Author

Kishore, Nishant, primary, Marqués, Domingo, additional, Mahmud, Ayesha, additional, Kiang, Mathew V., additional, Rodriguez, Irmary, additional, Fuller, Arlan, additional, Ebner, Peggy, additional, Sorensen, Cecilia, additional, Racy, Fabio, additional, Lemery, Jay, additional, Maas, Leslie, additional, Leaning, Jennifer, additional, Irizarry, Rafael A., additional, Balsari, Satchit, additional, and Buckee, Caroline O., additional

Published
2018
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143. Population mobility reductions associated with travel restrictions during the Ebola epidemic in Sierra Leone: use of mobile phone data

Author

Peak, Corey M, primary, Wesolowski, Amy, additional, zu Erbach-Schoenberg, Elisabeth, additional, Tatem, Andrew J, additional, Wetter, Erik, additional, Lu, Xin, additional, Power, Daniel, additional, Weidman-Grunewald, Elaine, additional, Ramos, Sergio, additional, Moritz, Simon, additional, Buckee, Caroline O, additional, and Bengtsson, Linus, additional

Published
2018
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147. Productive disruption: opportunities and challenges for innovation in infectious disease surveillance

Author

Buckee, Caroline O., primary, Cardenas, Maria I E, additional, Corpuz, June, additional, Ghosh, Arpita, additional, Haque, Farhana, additional, Karim, Jahirul, additional, Mahmud, Ayesha S., additional, Maude, Richard J, additional, Mensah, Keitly, additional, Motaze, Nkengafac Villyen, additional, Nabaggala, Maria, additional, Metcalf, Charlotte Jessica Eland, additional, Mioramalala, Sedera Aurélien, additional, Mubiru, Frank, additional, Peak, Corey M., additional, Pramanik, Santanu, additional, Rakotondramanga, Jean Marius, additional, Remera, Eric, additional, Sinha, Ipsita, additional, Sovannaroth, Siv, additional, Tatem, Andrew J, additional, and Zaw, Win, additional

Published
2018
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148. Multinational patterns of seasonal asymmetry in human movement influence infectious disease dynamics

Author

Wesolowski, Amy, primary, zu Erbach-Schoenberg, Elisabeth, additional, Tatem, Andrew J., additional, Lourenço, Christopher, additional, Viboud, Cecile, additional, Charu, Vivek, additional, Eagle, Nathan, additional, Engø-Monsen, Kenth, additional, Qureshi, Taimur, additional, Buckee, Caroline O., additional, and Metcalf, C. J. E., additional

Published
2017
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149. Identifying climate drivers of infectious disease dynamics: recent advances and challenges ahead.

Author

Metcalf, C Jessica E, Metcalf, C Jessica E, Walter, Katharine S, Wesolowski, Amy, Buckee, Caroline O, Shevliakova, Elena, Tatem, Andrew J, Boos, William R, Weinberger, Daniel M, Pitzer, Virginia E, Metcalf, C Jessica E, Metcalf, C Jessica E, Walter, Katharine S, Wesolowski, Amy, Buckee, Caroline O, Shevliakova, Elena, Tatem, Andrew J, Boos, William R, Weinberger, Daniel M, and Pitzer, Virginia E

Abstract

Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

Published
2017

150. THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites.

Author

Chang, Hsiao-Han, Chang, Hsiao-Han, Worby, Colin J, Yeka, Adoke, Nankabirwa, Joaniter, Kamya, Moses R, Staedke, Sarah G, Dorsey, Grant, Murphy, Maxwell, Neafsey, Daniel E, Jeffreys, Anna E, Hubbart, Christina, Rockett, Kirk A, Amato, Roberto, Kwiatkowski, Dominic P, Buckee, Caroline O, Greenhouse, Bryan, Chang, Hsiao-Han, Chang, Hsiao-Han, Worby, Colin J, Yeka, Adoke, Nankabirwa, Joaniter, Kamya, Moses R, Staedke, Sarah G, Dorsey, Grant, Murphy, Maxwell, Neafsey, Daniel E, Jeffreys, Anna E, Hubbart, Christina, Rockett, Kirk A, Amato, Roberto, Kwiatkowski, Dominic P, Buckee, Caroline O, and Greenhouse, Bryan

Abstract

As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings.

Published
2017

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