Arik Kershenbaum

Publications (9) View all

• Source

  Available from: Arik Kershenbaum

  Article: A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

  Stefan Edlund, Matthew Davis, Judith V Douglas, Arik Kershenbaum, Narongrit Waraporn, Justin Lessler, James H Kaufman
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  ABSTRACT: BACKGROUND: The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. METHODS: This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence) built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data). The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation's Spatiotemporal Epidemiological Modeller (STEM). RESULTS: Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS) error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166-2 national subdivisions and with monthly time sampling. CONCLUSIONS: The high spatial resolution possible with state-of-the-art numerical models can identify regions most likely to require intervention due to climate changes. Higher-resolution surveillance data can provide a better understanding of how climate fluctuations affect malaria incidence and improve predictions. An open-source modelling framework, such as STEM, can be a valuable tool for the scientific community and provide a collaborative platform for developing such models.
  Malaria Journal 09/2012; 11(1):331. · 3.19 Impact Factor
• Article: Syntactic structure and geographical dialects in the songs of male rock hyraxes.

  Arik Kershenbaum, Amiyaal Ilany, Leon Blaustein, Eli Geffen
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  ABSTRACT: Few mammalian species produce vocalizations that are as richly structured as bird songs, and this greatly restricts the capacity for information transfer. Syntactically complex mammalian vocalizations have been previously studied only in primates, cetaceans and bats. We provide evidence of complex syntactic vocalizations in a small social mammal: the rock hyrax (Procavia capensis: Hyracoidea). We adopted three algorithms, commonly used in genetic sequence analysis and information theory, to examine the order of syllables in hyrax calls. Syntactic dialects exist, and the syntax of hyrax calls is significantly different between different regions in Israel. Call syntax difference is positively correlated to geographical distance over short distances. No correlation is found over long distances, which may reflect limited dispersal movement. These findings indicate that rich syntactic structure is more common in the vocalizations of mammalian taxa than previously thought and suggest the possibility of vocal production learning in the hyrax.
  Proceedings of the Royal Society B: Biological Sciences 04/2012; 279(1740):2974-81. · 5.41 Impact Factor
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  Available from: Arik Kershenbaum

  Article: Modelling transmission of vector-borne pathogens shows complex dynamics when vector feeding sites are limited.

  Arik Kershenbaum, Lewi Stone, Richard S Ostfeld, Leon Blaustein
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  ABSTRACT: The relationship between species richness and the prevalence of vector-borne disease has been widely studied with a range of outcomes. Increasing the number of host species for a pathogen may decrease infection prevalence (dilution effect), increase it (amplification), or have no effect. We derive a general model, and a specific implementation, which show that when the number of vector feeding sites on each host is limiting, the effects on pathogen dynamics of host population size are more complex than previously thought. The model examines vector-borne disease in the presence of different host species that are either competent or incompetent (i.e. that cannot transmit the pathogen to vectors) as reservoirs for the pathogen. With a single host species present, the basic reproduction ratio R(0) is a non-monotonic function of the population size of host individuals (H), i.e. a value [Formula: see text] exists that maximises R(0). Surprisingly, if [Formula: see text] a reduction in host population size may actually increase R(0). Extending this model to a two-host species system, incompetent individuals from the second host species can alter the value of [Formula: see text] which may reverse the effect on pathogen prevalence of host population reduction. We argue that when vector-feeding sites on hosts are limiting, the net effect of increasing host diversity might not be correctly predicted using simple frequency-dependent epidemiological models.
  PLoS ONE 01/2012; 7(5):e36730. · 4.09 Impact Factor
• Article: Predator guild does not influence orangutan alarm call rates and combinations

  AdrianoR. Lameira, Han Vries, MadeleineE. Hardus, CedricP.A. Hall, Tatang Mitra-Setia, BerryM. Spruijt, Arik Kershenbaum, ElisabethH.M. Sterck, Maria Noordwijk, Carel Schaik, SergeA. Wich
  Behavioral Ecology and Sociobiology 01/2012; · 3.18 Impact Factor
• Article: Unraveling seasonality in population averages: an examination of seasonal variation in glucose levels in diabetes patients using a large population-based data set.

  Anne Kershenbaum, Arik Kershenbaum, Jalal Tarabeia, Nili Stein, Idit Lavi, Gad Rennert
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  ABSTRACT: It has been shown that the population average blood glucose level of diabetes patients shows seasonal variation, with higher levels in the winter than summer. However, seasonality in the population averages could be due to a tendency in the individual to seasonal variation, or alternatively due to occasional high winter readings (spiking), with different individuals showing this increase in different winters. A method was developed to rule out spiking as the dominant pattern underlying the seasonal variation in the population averages. Three years of data from three community-serving laboratories in Israel were retrieved. Diabetes patients (N = 3243) with a blood glucose result every winter and summer over the study period were selected. For each individual, the following were calculated: seasonal average glucose for all winters and summers over the period of study (2006-2009), winter-summer difference for each adjacent winter-summer pair, and average of these five differences, an index of the degree of spikiness in the pattern of the six seasonal levels, and number of times out of five that each winter-summer difference was positive. Seasonal population averages were examined. The distribution of the individual's differences between adjacent seasons (winter minus summer) was examined and compared between subgroups. Seasonal population averages were reexamined in groups divided according to the index of the degree of spikiness in the individual's glucose pattern over the series of seasons. Seasonal population averages showed higher winter than summer levels. The overall median winter-summer difference on the individual level was 8 mg/dL (0.4 mmol/L). In 16.9% (95% confidence interval [CI]: 15.6-18.2%) of the population, all five winter-summer differences were positive versus 3.6% (95% CI: 3.0-4.2%) where all five winter-summer differences were negative. Seasonal variation in the population averages was not attenuated in the group having the lowest spikiness index; comparison of the distributions of the winter-summer differences in the high-, medium-, and low-spikiness groups showed no significant difference (p = .213). Therefore, seasonality in the population average blood glucose in diabetes patients is not just the result of occasional high measurements in different individuals in different winters, but presumably reflects a general periodic tendency in individuals for winter glucose levels to be higher than summer levels.
  Chronobiology International 05/2011; 28(4):352-60. · 4.03 Impact Factor