Newest publications
Improving accuracy, stability, and practicability of poverty-targeting tools in the context of vietnamese ethnic minorities
(2025) Duong, Be Thanh; Zeller, Manfred
Poverty-targeting tools (PTTs) are essential tools used globally to identify households below established poverty benchmarks, such as food consumption or monetary standards, through simple and verifiable indicators. These tools enable social programs, ranging from cash transfers to healthcare and educational supports, to effectively and quickly deliver urgent support to the households most in need. However, despite the significant improvements made over time, current PTTs face some critical limitations that undermine their accuracy performance in both laboratory and field conditions.
First, current efforts to enhance PTT accuracy through algorithmic improvements appear to be reaching a plateau. The Weight of Evidence (WOE) transformation technique has demonstrated success in optimizing the predictive power of input variables and potentially improving the accuracy of the prediction model across other domains, but this methodology remains underexplored in the poverty targeting field. Additionally, most existing PTTs lack transparent and user-friendly scoring systems. The score-scaling technique, doubling-the-odds, commonly paired with WOE in credit scoring, provides a logical and interpretable relationship between scores and outcome probabilities, yet it is rarely applied to the development of PTTs.
Second, although the performance stability of PTTs is critical for ensuring their reliability and robustness in different datasets and real-world applications, this aspect remains insufficiently addressed in current research. Most existing studies rely on hold-out validation, which assesses the model’s performance based on a single random draw of a training-testing split. This approach offers limited insight into performance variability and restricts developers from making timely model adjustments. While k-fold cross-validation, a technique widely adopted in machine learning, offers a more comprehensive assessment of model stability and facilitates the fine-tuning of prediction models, this technique remains underutilized in poverty-targeting research.
Third, the predictive accuracy of PTTs in the real world is significantly impacted by their practicability, namely the simplicity and verifiability of their indicators, but this aspect is often assumed rather than empirically validated. Currently, developers select indicators based on theoretical assumptions about simplicity and verifiability, without systematically validating these assumptions with frontline users. In addition, various contextual factors may influence the practicability of PTTs, ultimately affecting their overall predictive accuracy in practice. Despite this, no studies have thoroughly explored this dimension.
To address these critical gaps, this dissertation aims to enhance the predictive performance of PPTs in both controlled research environments and real-world implementation settings. The research focuses on advancing fundamental dimensions of PTT effectiveness: technical accuracy, performance stability, transparency, and practicability. The research is situated in the context of ethnic minority communities in Vietnam, which experience the highest poverty rates and are a major concern for national poverty reduction programs. To achieve this overarching goal, this dissertation pursues the following interconnected sub-objectives: (1) Examine the efficacy of applying the WOE transformation method to improve the accuracy of PPTs; (2) Explore the combination of k-fold cross-validation with the WOE technique to ensure high and consistent performance PTTs with transparent and interpretable scoring systems; (3) Evaluate the practicability (simplicity and verifiability) of the PPTs and identify the key determinants impacting their practicability in field conditions, particularly in the context of Khmer communities in Southern Vietnam. These objectives are addressed through three scientific articles, presented respectively in Chapters 2 through 4 in this dissertation.
The first research component of this dissertation is presented in Chapter 2, which examines the adaptation of the WOE technique in constructing high-accuracy PTTs. This research introduces a comprehensive approach, called the WOE (Logit) method, to develop PTTs based on international and national poverty lines. The WOE (Logit) method integrates the WOE technique with other techniques such as logistic regression, the indicator selection approach based on c-statistic value, and a score-scaling technique of doubling the odds. The resulting PTTs are evaluated against well-known methods such as the Simple Poverty Scorecard, Proxy Means Test, and Poverty Assessment Tool. The results show that the WOE (Logit) method yields higher accuracy, specifically improving identification rates by 1.9–5.9 percentage points for households and 1.5–3.3 percentage points for individuals. This finding contributes a valuable alternative methodology for more accurate poverty targeting.
Chapter 3 explores the effectiveness of integrating k-fold cross-validation into the WOE (Logit) method in constructing high-accuracy and stable-performance PTTs with transparent scoring mechanisms for ethnic minorities in Vietnam (EMP tools). This research integrates a 5-fold cross-validation technique into the WOE (Logit) method to assess predictive performance and its variation. Two indicator selection strategies are compared based on the results of 5-fold cross-validation to find out the best prediction models, high-predictive power, and low performance variation, to develop EMP tools: one based on the highest c-statistic value (MaxC) and the other on the smallest Akaike Information Criterion (MinAIC). The results indicate that both indicator selection approaches yield high predictive power with minimal differences between them. However, the MinAIC approach shows a significantly lower performance variation in small urban datasets and remains slightly more stable in large rural datasets. Based on these results, MinAIC-based models are selected to design the EMP tools by applying the score-scaling technique of doubling-the-odds. Independent testing further validates this choice: the MinAIC models outperform their MaxC counterparts in terms of predictive power and standard error across rural and urban settings. When tested out-of-sample, EMP tools outperform the Vietnamese government’s current models while using one-third the number of indicators. Crucially, the EMP tools also feature a transparent and user-friendly scoring mechanism, which the government's tools lack. These results underscore the value of incorporating k-fold cross-validation to assess both accuracy and stability during model selection. Moreover, this study demonstrates that this integrated strategy effectively develops transparent PTTs with high accuracy and stable performance.
The third article in Chapter 4 evaluates the practicability of the EMP tools developed in Chapter 3 through a field study in Khmer communities in the Vietnamese Mekong Delta. Employing both quantitative and qualitative methods, this study examines enumerators’ perceptions of indicator simplicity and verifiability. Quantitative data are analyzed using Likert scales, Factor Analysis, and Ordinary Least Squares regression, while qualitative data are analyzed using a thematic approach. The findings reveal a complex landscape of practicability that challenges conventional assumptions about indicator simplicity and verifiability. While EMP tools are generally perceived as practical, with over half of enumerators affirming the straightforwardness and verifiability of most indicators, significant variations exist across different types of indicators. Some commonly assumed simple indicators (e.g., cellphone ownership, job type) are rated low in verifiability, while more complex indicators (e.g., land ownership) are seen as more practical than anticipated. Qualitative insights highlight the vital role of local knowledge, particularly from village managers, in verifying high-risk indicators. The characteristics of enumerators (such as ethnicity, age, authority level of enumerators, and prior poverty-targeting experience) are significant determinants of overall tool practicability. These findings contribute a mixed-methods framework for pre-assessing PTT practicability and suggest solutions for improving tool practicability through more targeted enumerator selection.
In sum, the dissertation achieves its three sub-objectives by demonstrating that: (1) the WOE (Logit) method enhances the predictive accuracy of PTTs; (2) Incorporating the k-fold cross-validation alongside the WOE (Logit) method reduces performance variation, enabling the development of high-accuracy and stable PTTs with transparent and use-friendly scoring systems; (3) Practical field assessments confirm that while the EMP tools are generally practical, conventional assumptions about indicator simplicity may require re-examination. Furthermore, enumerator characteristics significantly impact the practicability of the tools, suggesting their consideration in enumerator recruitment processes to optimize the tool’s practicability during implementation.
This dissertation makes substantial theoretical and empirical contributions to poverty targeting research and practice through three key aspects. First, it provides compelling empirical evidence demonstrating how techniques so far have been underutilized in poverty identification; that is, the WOE technique and the k-fold cross-validation can enhance both the accuracy, transparency, and stability of poverty targeting, while highlighting the critical importance of field-based practicability assessments before implementing PPTs. Second, the research contributes an integrated methodological framework that integrates the WOE (Logit) method with the k-fold cross-validation and a mixed-methods approach of practicability assessment. This framework serves as a robust foundation for developing transparent PTTs that consistently deliver high accuracy and stable performance across diverse contexts. Third, the study not only delivers high-accuracy, stable-performance, and practical PTTs with a transparent and user-friendly scoring mechanism for ethnic minorities in Vietnam, but also offers actionable insights and strategies to maximize these tools’ practicability in real-world settings, ultimately supporting their accuracy performance during implementation. While focused on ethnic minorities in Vietnam, the broader implications of this research extend beyond this context, offering a replicable framework for constructing context-appropriate PTTs that perform accurately and reliably across diverse conditions while remaining practically feasible for frontline implementation.
Development of new inhibitors directed against key enzymes of human pathogens
(2025) Herzog, Anna-Maria; Fritz, Günter
Infectious diseases are one of the biggest threats to global health. The unpredictable emergence and rapid spread of viral infections, as well as the increasing frequency of antimicrobial resistance in bacterial infections, are particularly challenging due to the lack of adequate treatment options. To address these limitations, the rapid development of novel pharmaceuticals directed against essential, highly conserved enzymes of human pathogens is of urgent need. Fragment-based drug discovery (FBDD) is an approach to de novo drug design. After identifying simple, low-molecular-weight molecules (fragments) that bind the target protein, selective, high-affinity lead compounds must be developed through optimization. The objectives of this study include investigating potential inhibitors of two proteins, the papain-like protease (PLpro) of the Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) and a bacterial respiratory enzyme, the Na+-translocating NADH:ubiquinone oxidoreductase (NQR), as well as methods to support the fragment-to-lead optimization process.
The PLpro is a key enzyme of SARS-CoV-2 that ensures viral replication and suppresses the antiviral immune response. It is responsible for the proteolytic processing of the non-structural proteins 1-3 (nsp1-3) of the viral polyproteins, which are important for the replication and transcription complex. Correct formation of this complex is essential for replication of the viral genome and transcription of structural genes. Furthermore, the PLpro antagonizes the interferon stimulated antiviral response through specific cleavage of the interferon stimulated gene 15 (ISG15). ISG15 is conjugated to host and viral proteins during viral infection to promote the immune response and disrupt the proper function of viral proteins. Preventing polyprotein processing and ISG15 cleavage by inhibiting the PLpro represents a promising therapeutic option for the coronavirus disease 2019 (COVID-19). The PLpro cleavage activity in presence of the hop-derived compounds xanthohumol (XN), isoxanthohumol (IX), 6-prenylnaringenin (6PN), and 8-prenylnaringenin (8PN) was determined in fluorescence-based assays using the peptide Z-RLRGG-AMC, or ISG15-rhodamine and reveals inhibition by all four compounds. Western blot analysis of interferon β treated Human Embryonic Kidney (HEK) cell lysates validates the inhibition of ISG15 cleavage through IXN. Antiviral activity of XN and 6PN is shown in infection models using Caco-2 cells. Therefore, these hop-derived compounds are promising starting points for developing new antiviral drugs.
The NQR is a central enzyme in the energy metabolism of bacteria, including pathogens such as Vibrio cholerae, and multidrug-resistant Klebsiella pneumoniae and Pseudomonas aeruginosa. By coupling the oxidation of NADH with the reduction of ubiquinone, it translocates sodium ions or protons from the cytoplasm in the periplasm. Through this translocation, electrochemical gradients, the sodium or proton motive force are generated across the cytoplasmic membrane. These motive forces are required for several metabolic processes, like substrate uptake, ATP synthesis, motility, or drug efflux by multidrug-resistant (MDR) efflux pumps. Interrupting the binding of NADH and, consequently, the generation of the electrochemical gradients could be a promising approach for developing novel antibiotics and new treatment options for multidrug-resistant pathogens. The compound [1-(4-chlorophenyl)-1H-1,2,3-triazol-4-yl]methanol (CPTM) was selected from the fragments identified during a crystallographic screening against the NqrF subunit of V. cholerae. The fragment binds in the part of the NADH-binding pocket where the adenosine residue of the NADH usually binds. It inhibits the NADH-oxidizing activity of the NqrF subunits of V. cholerae, K. pneumoniae, and P. aeruginosa, as well as the NQR complex of V. cholerae in a mixed mode of inhibition, with a significantly stronger inhibitory effect on the NQR complex. In growth assays, CPTM exhibited antibacterial activity against V. cholerae, and multidrug-resistant strains of K. pneumoniae, and P. aeruginosa. In a combinatorial treatment, the efficacy of erythromycin increases when combined with CPTM in V. cholerae and K. pneumoniae but decreases in P. aeruginosa. The inhibition by occupying the NADH-binding pocket and the identification of the promising inhibitor CPTM are basis for structure-based optimization to develop antibacterial agents. Specific NQR inhibition opens the door to combinatorial therapy options for multidrug-resistant pathogens, which could restore the efficacy of current antibiotics.
In FBDD, the identification of initial hits is followed by an optimization to improve their affinity, specificity, and physicochemical properties through fragment growing, merging, or linking strategies. To support single steps of the subsequent analysis to identify the candidates with improved properties, many computational tools are available. EvaMol is a software that integrates several of these tools to cover the entire evaluation. It prepares a receptor and the database of input molecules, obtained by the optimization. In the following docking step, the best-fitting pose of each molecule is calculated. Then, two independent scoring algorithms assess the binding of the docked molecules. Finally, physicochemical properties and ligand efficiency metrics are calculated. This helps to prioritize the candidate molecules with the most promising features and accelerates fragment-to-lead development in early drug discovery.
Overall, the findings of this study lay the foundation for the development of novel antiviral and antibacterial pharmaceuticals and provide a tool to facilitate the optimization process in FBDD pipelines. This contributes to the urgent need for novel treatments caused by infectious diseases.
Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant
(2022) Chang, Che-Wei; Fridman, Eyal; Mascher, Martin; Himmelbach, Axel; Schmid, Karl
Determining the extent of genetic variation that reflects local adaptation in crop-wild relatives is of interest for the purpose of identifying useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley ( Hordeum vulgare L. ssp. spontaneum ) populations of the Southern Levant using genotyping by sequencing (GBS) of 244 accessions in the Barley 1K+ collection. The inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association between lower gene flow rates and geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was solely attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). When conditioned on population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify adaptation signatures. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions, which have reduced recombination, of the chromosomes 3H, 4H, and 5H. However, selection signatures mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges had a limited effect on the genomic diversity of wild barley. This highlighted the importance of nonselective forces in genetic differentiation.
Assessing the between-country genetic correlation in maize yield using German and Polish official variety trials
(2022) Malik, Waqas Ahmed; Buntaran, Harimurti; Przystalski, Marcin; Lenartowicz, Tomasz; Piepho, Hans-Peter
Official variety testing is performed in many countries by statutory agencies in order to identify the best candidates and make decisions on the addition to the national list. Neighbouring countries can have similarities in agroecological conditions, so it is worthwhile to consider a joint analysis of data from national list trials to assess the similarity in performance of those varieties tested in both countries. Here, maize yield data from official German and Poland variety trials for cultivation and use (VCU) were analysed for the period from 1987 to 2017. Several statistical models that incorporate environmental covariates were fitted. The best fitting model was used to compute estimates of genotype main effects for each country. It is demonstrated that a model with random genotype-by-country effects can be used to borrow strength across countries. The genetic correlation between cultivars from the two countries equalled 0.89. The analysis based on agroecological zones showed high correlation between zones in the two countries. The results also showed that 22 agroecological zones in Germany can be merged into five zones, whereas the six zones in Poland had very high correlation and can be considered as a single zone for maize. The 43 common varieties which were tested in both countries performed equally in both countries. The mean performances of these common varieties in both countries were highly correlated.
Split N application and DMP based nitrification inhibitors mitigate N2O losses in a soil cropped with winter wheat
(2022) Guzman-Bustamante, Ivan; Schulz, Rudolf; Müller, Torsten; Ruser, Reiner
Nitrogen (N) fertilization to crops might lead to formation and release of reactive N—e.g. nitrate, ammonium, ammonia, nitrous oxide (N2O) —, contributing to eutrophication, atmospheric pollution, and climate change. Use of nitrification inhibitors and splitting of N fertilizer may reduce the N2O emission from arable soils cropped with winter wheat. We tested different N fertilizers treated with 3,4-dimethylpyrazol phosphate (DMPP) and 3,4-dimethylpyrazol succinic acid (DMPSA) by applying 180 kg N ha−1 in different N splitting strategies in a full annual field experiment on a loamy soil in Southwest Germany. A threefold split fertilization led to an emission of 2.3 kg N2O–N ha−1 a−1 (corresponding to a reduction of 19%) compared to a single application of ammonium sulphate nitrate (ASN) (p = 0.07). A single application rate of ASN with DMPP resulted in an emission of 1.9 kg N2O–N ha−1 a−1 and reduced N2O emissions from an ASN treatment without NI by 33%. Calcium ammonium nitrate (CAN) with DMPSA reduced N2O emissions during the vegetation period by 38% compared to CAN without a nitrification inhibitor, but this was offset by high emissions after harvest, which was driven by soil tillage with an annual reduction of 26% (CAN: 2.9 kg N2O–N ha−1 a−1; CAN + DMPSA: 2.1 kg N2O–N ha−1 a−1; p = 0.11). Among our tested treatments, a twofold split application of ASN with DMPP efficiently reduced N2O emissions and maintained grain yield when compared to the traditional system with threefold application without nitrification inhibitor. Despite resulting in lower protein contents in the twofold split application, this treatment should be further investigated as a potential compromise between wheat yield and quality optimization and climate protection.