Tan, K. B. | Search bioRxiv

bioRxiv2026

Estimating spatially adjusted temperature-dependent time-varying reproduction numbers for vector-borne diseases

Estimating the effective reproduction number is crucial for understanding and managing infectious disease outbreaks. For vector-borne diseases like dengue, transmission depends on environmental and spatial conditions: temperature affects the extrinsic incubation period in mosquitoes, altering transmission timing, while spatial proximity can lead to clusters of transmission. We integrated a temperature-dependent (TD) generation time (GT) distribution and a spatial decay function weighting transmission likelihood by distance into the Wallinga & Teunis estimation framework. Simulations compared scenarios where the true generation time for spatially adjusted disease cases were TD or temperature independent (TI), versus their corresponding model assumptions. Daily reproduction numbers (Rt) estimated were evaluated via percent error against true values. We found error to be predominantly driven by variance rather than bias, indicating that stochastic uncertainty in infector assignment was the primary driver of inaccuracies rather than systematic model miscalibration. Assuming a spatial weighting function assigning higher probabilities of transmission to geographically close infector-infectee pairs (Gaussian spatial decay) percent errors measuring deviation between estimated and true Rt outperformed those of alternative spatial kernels. Mis-specifying temperature-dependence under a Gaussian spatial kernel yielded higher errors when the ground truth was TD (16-38% vs 36-58% deviation), and similar errors when it was TI (32-52% vs 35-56% deviation), indicating limited sensitivity to temperature dependence when it was not present in the underlying transmission process. Application to dengue case data in Singapore showed that spatially adjusted models produced more variable Rt trajectories than time-series smoothing approaches, with Gaussian decay yielding more stable estimates than exponential decay and the TD model producing modest refinements, suggesting that explicitly modeling spatial heterogeneity and TD transmission dynamics increases responsiveness to even fluctuations in case counts. Our framework is robust across climates, shown by simulations using a broader temperature range, and suggests a useful application in retrospective analyses.

ecology↗

bioRxiv2022

PAX6 LIMITS THE COMPETENCE OF DEVELOPING CEREBRAL CORTICAL CELLS

The development of stable specialized cell types in multicellular organisms relies on mechanisms controlling inductive intercellular signals and the competence of cells to respond to such signals. In developing cerebral cortex, progenitors generate only glutamatergic excitatory neurons despite being exposed to signals with the potential to initiate the production of other neuronal types, suggesting that their competence is limited. Here we tested the hypothesis that this limitation is due to their expression of transcription factor Pax6. We used bulk and single cell RNAseq to show that conditional cortex-specific Pax6 deletion from the onset of cortical neurogenesis allowed some progenitors to generate abnormal lineages resembling those normally found outside the cortex. Analysis of selected gene expression showed that the changes occurred in specific spatiotemporal patterns. We then compared the responses of control and Pax6-deleted cortical cells to in vivo and in vitro manipulations of extracellular signals. We found that Pax6 loss increased cortical progenitors competence to generate inappropriate lineages in response to extracellular factors normally present in developing cortex, including the morphogens Shh and Bmp4. Regional variation in the levels of these factors could explain spatiotemporal patterns of fate change following Pax6 deletion in vivo. We propose that Pax6s main role in developing cortical cells is to minimize the risk of their development being derailed by the potential side-effects of morphogens engaged contemporaneously in other essential functions.

neuroscience↗